commit 69820f75c79a34dbe1ee1ce0d31d4dfd468d8f6d parent 447ada7536c5a78bd4a03e9a9ec6e30f37eaaffc Author: miksa <milutin@popovic.xyz> Date: Sun, 1 May 2022 13:00:08 +0200 done some fitting for freezing fritz Diffstat:
12 files changed, 7039 insertions(+), 0 deletions(-)
diff --git a/freezing_fritz/.ipynb_checkpoints/TurnUpTheHeat_Evaluation-checkpoint.ipynb b/freezing_fritz/.ipynb_checkpoints/TurnUpTheHeat_Evaluation-checkpoint.ipynb @@ -0,0 +1,657 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib as mpl\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.pyplot import ion\n", + "from scipy.signal import convolve2d\n", + "import pandas as pd\n", + "import seaborn as sn\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Freezing Fritz, is a pretty cool guy. He has one problem, though. In his house, it is quite often too cold or to hot during the night. Then he has to get up and open or close his windows or turn on the heat. Needless to say, he would like to avoid this. \n", + "\n", + "However, his flat has three doors that he can keep open or closed, it has four radiators, and four windows. It seems like there are endless possibilities of prepping the flat for whatever temperature the night will have. \n", + "\n", + "Fritz, does not want to play his luck any longer and decided to get active. He recorded the temperature outside and inside of his bedroom for the last two years. Now he would like to find an prediction that, given the outside temperature, as well as a certain configuration of his flat, tells him how cold or warm his bedroom will become.\n", + "\n", + "Can you help Freezing Fritz to find blissful sleep?\n", + "\n", + "\n", + "Let us first look at the situation. In the lecture notes you will find the experiment that Fritz carried out described in 8 cases." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For the experiment, we first load the data" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>Window 1</th>\n", + " <th>Window 2</th>\n", + " <th>Window 3</th>\n", + " <th>Window 4</th>\n", + " <th>Heat Control 1</th>\n", + " <th>Heat Control 2</th>\n", + " <th>Heat Control 3</th>\n", + " <th>Heat Control 4</th>\n", + " <th>Door 1</th>\n", + " <th>Door 2</th>\n", + " <th>Door 3</th>\n", + " <th>Temperature Outside</th>\n", + " <th>Temperature Bed</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>0.0</td>\n", + " <td>1.0</td>\n", + " <td>1.0</td>\n", + " <td>1.0</td>\n", + " <td>4.0</td>\n", + " <td>3.0</td>\n", + " <td>5.0</td>\n", + " <td>0.0</td>\n", + " <td>1.0</td>\n", + " <td>0.0</td>\n", + " <td>1.0</td>\n", + " <td>21.421148</td>\n", + " <td>-20.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>0.0</td>\n", + " <td>1.0</td>\n", + " <td>5.0</td>\n", + " <td>3.0</td>\n", + " <td>1.0</td>\n", + " <td>1.0</td>\n", + " <td>0.0</td>\n", + " <td>13.853981</td>\n", + " <td>-20.0</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>1.0</td>\n", + " <td>0.0</td>\n", + " <td>1.0</td>\n", + " <td>1.0</td>\n", + " <td>3.0</td>\n", + " <td>1.0</td>\n", + " 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0.0 0.0 0.0 0.0 0.0 1.0 \n", + "2 1.0 0.0 1.0 1.0 3.0 1.0 \n", + "3 1.0 1.0 1.0 1.0 3.0 0.0 \n", + "4 1.0 1.0 1.0 1.0 0.0 5.0 \n", + "\n", + " Heat Control 3 Heat Control 4 Door 1 Door 2 Door 3 \\\n", + "0 5.0 0.0 1.0 0.0 1.0 \n", + "1 5.0 3.0 1.0 1.0 0.0 \n", + "2 3.0 5.0 1.0 0.0 0.0 \n", + "3 1.0 0.0 1.0 0.0 1.0 \n", + "4 5.0 5.0 1.0 1.0 1.0 \n", + "\n", + " Temperature Outside Temperature Bed \n", + "0 21.421148 -20.0 \n", + "1 13.853981 -20.0 \n", + "2 -1.493988 -20.0 \n", + "3 1.787096 -20.0 \n", + "4 -3.007195 -20.0 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_train_Temperature = pd.read_csv('data_train_Temperature.csv')\n", + "data_test_Temperature = pd.read_csv('data_test_Temperature.csv')\n", + "data_test_Temperature.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us look at this closely" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>Window 1</th>\n", + " <th>Window 2</th>\n", + " <th>Window 3</th>\n", + " <th>Window 4</th>\n", + " <th>Heat Control 1</th>\n", + " <th>Heat Control 2</th>\n", + " <th>Heat Control 3</th>\n", + " <th>Heat Control 4</th>\n", + " <th>Door 1</th>\n", + " <th>Door 2</th>\n", + " <th>Door 3</th>\n", + " <th>Temperature Outside</th>\n", + " <th>Temperature Bed</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>count</th>\n", + " <td>1095.000000</td>\n", + " <td>1095.000000</td>\n", + " 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<td>21.992202</td>\n", + " <td>33.882457</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " Window 1 Window 2 Window 3 Window 4 Heat Control 1 \\\n", + "count 1095.000000 1095.000000 1095.000000 1095.000000 1095.000000 \n", + "mean 0.515982 0.523288 0.519635 0.490411 2.518721 \n", + "std 0.499973 0.499686 0.499843 0.500136 1.716509 \n", + "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 0.000000 0.000000 0.000000 1.000000 \n", + "50% 1.000000 1.000000 1.000000 0.000000 3.000000 \n", + "75% 1.000000 1.000000 1.000000 1.000000 4.000000 \n", + "max 1.000000 1.000000 1.000000 1.000000 5.000000 \n", + "\n", + " Heat Control 2 Heat Control 3 Heat Control 4 Door 1 \\\n", + "count 1095.000000 1095.000000 1095.000000 1095.000000 \n", + "mean 2.463014 2.585388 2.528767 0.509589 \n", + "std 1.668685 1.702178 1.733328 0.500136 \n", + "min 0.000000 0.000000 0.000000 0.000000 \n", + "25% 1.000000 1.000000 1.000000 0.000000 \n", + "50% 2.000000 3.000000 2.000000 1.000000 \n", + "75% 4.000000 4.000000 4.000000 1.000000 \n", + "max 5.000000 5.000000 5.000000 1.000000 \n", + "\n", + " Door 2 Door 3 Temperature Outside Temperature Bed \n", + "count 1095.000000 1095.000000 1095.000000 1095.000000 \n", + "mean 0.499543 0.518721 8.572088 19.852056 \n", + "std 0.500228 0.499878 7.898873 6.926361 \n", + "min 0.000000 0.000000 -4.993865 0.590713 \n", + "25% 0.000000 0.000000 1.586682 14.603950 \n", + "50% 0.000000 1.000000 8.509676 20.950144 \n", + "75% 1.000000 1.000000 15.309044 25.284787 \n", + "max 1.000000 1.000000 21.992202 33.882457 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_train_Temperature.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We use the correlation matrix again to see how each of the parameters of the problem affect the temperature in the bedroom. We also look at how the trade-off between outside and inside temperature is affected by some of the parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 864x864 with 2 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<Figure size 864x864 with 0 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 416.875x360 with 6 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 440.125x360 with 6 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 412x360 with 6 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "corrMatrix = data_train_Temperature.corr()\n", + "plt.figure(figsize = (12,12))\n", + "palette = sn.diverging_palette(20, 220, n=256)\n", + "sn.heatmap(corrMatrix, annot=False, cmap = palette, vmin = -1, vmax = 1)\n", + "plt.show()\n", + "\n", + "plt.figure(figsize = (12,12))\n", + "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Window 1')\n", + "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Heat Control 1')\n", + "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Door 1')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We do not have that many data points. We should therefore first reduce the dimensionality of the problem.\n", + "\n", + "My idea is to interpolate over the data but weigh it according to my observations. So I give low weights to windows 2 and 3. Same with door 3.\n", + "Then " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We predict on the first 80% of the data and then validate on the remaining 20%" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "observations = data_train_Temperature.shape[0]\n", + "simple_data_set = data_train_Temperature.copy().drop(range(int(0.2*observations)), axis = 0)\n", + "\n", + "def predict(data):\n", + " simple_test_set = data.copy()\n", + "\n", + " #some parameters are more important to fit right than others. (In our case, window 1 and doors 1 and 2)\n", + " weights = np.ones(12)\n", + " weights[0] = 10 # Window 1\n", + " weights[1] = 1 # Window 2\n", + " weights[2] = 1 # Window 3\n", + " weights[3] = 10 # Window 4\n", + " weights[4] = 1 # Heat 1\n", + " weights[5] = 1 # Heat 2\n", + " weights[6] = 1 # Heat 3\n", + " weights[7] = 0 # Heat 4\n", + " weights[8] = 10 # Door 1\n", + " weights[9] = 10 # Door 2\n", + " weights[10] = 1 # Door 3\n", + " weights[11] = 1 # Temp Out \n", + "\n", + " for k in range(simple_test_set.shape[0]):\n", + " value = 0;\n", + " totaldist = 0\n", + " \n", + " \n", + " for j in range(simple_data_set.values.shape[0]):\n", + " value = value + simple_data_set.values[j,-1]/(np.linalg.norm(weights*simple_data_set.values[j,:-1] - weights*simple_test_set.values[k,:-1]))**4\n", + " totaldist = totaldist + 1/(np.linalg.norm(weights*simple_data_set.values[j,:-1] - weights*simple_test_set.values[k,:-1]))**4\n", + " simple_test_set.values[k, -1] = np.max([value/totaldist, simple_data_set.values[j,-2]])\n", + " \n", + " \n", + " return simple_test_set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we compute error on validation set:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.25879966076991" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "validation_set = data_train_Temperature.copy().drop(range(int(0.2*observations), observations), axis = 0)\n", + "res = predict(validation_set)\n", + "# root mean square error:\n", + "np.linalg.norm(res.values[:,-1] - validation_set.values[:,-1])/np.sqrt(len(res.values[:,-1]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The algorithm, was not very sophisticated, nonetheless I came within an accuracy of 3.5 degrees. For me this seems acceptable. \n", + "Maybe you can help Freezing Fritz even more?\n", + "\n", + "I will just store my prediction on the test set now:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "#make prediction \n", + "prediction = predict(data_test_Temperature)\n", + "predicted_Temperatures = prediction.values[:,-1]\n", + " \n", + "np.savetxt('PhilippPetersens_Temperature_prediction.csv', predicted_Temperatures, delimiter=',') " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/freezing_fritz/PhilippPetersens_Temperature_prediction.csv b/freezing_fritz/PhilippPetersens_Temperature_prediction.csv @@ -0,0 +1,100 @@ +2.495298942681507270e+01 +2.202287394318002001e+01 +1.119032922180299394e+01 +1.317611109438733408e+01 +9.847456399540417848e+00 +1.622489100390505712e+01 +1.923886006168768503e+01 +2.455749904842414466e+01 +1.544823668958957974e+01 +1.079003704453963586e+01 +2.356896444935568269e+01 +1.923064249847339013e+01 +9.847456399540417848e+00 +2.750063310112694026e+01 +2.433295760903009963e+01 +2.763580864415146010e+01 +9.847456399540417848e+00 +2.731496153160763640e+01 +2.878020038253021085e+01 +2.693419387884156890e+01 +2.453213747497807162e+01 +1.069022117561550189e+01 +2.633060901734536685e+01 +1.436132703701620272e+01 +9.847456399540417848e+00 +1.908567772001278939e+01 +1.665912658327030371e+01 +2.375008606255414279e+01 +1.321067485743704495e+01 +1.064761645008973368e+01 +2.421010965823588634e+01 +1.314387606021042743e+01 +2.623601939920013493e+01 +2.597798293126759006e+01 +2.654343268992734295e+01 +1.827856485656776542e+01 +1.127070091665119023e+01 +1.581618223683121371e+01 +1.612202013917329069e+01 +2.514215479631798189e+01 +2.085304020232178956e+01 +1.692531726749313847e+01 +1.365674005259735324e+01 +2.353147190092649055e+01 +1.887438043572676349e+01 +1.918674911219049406e+01 +9.847456399540417848e+00 +2.247815667437288667e+01 +1.506244794029807466e+01 +2.132609878115086488e+01 +2.036506140666567077e+01 +2.807819902099255671e+01 +1.289335175225979135e+01 +2.481185501619952305e+01 +2.247913125625554187e+01 +9.847456399540417848e+00 +1.254948500758728080e+01 +1.092241496083455310e+01 +2.077511150731235290e+01 +1.126502488911739164e+01 +2.007844784060781507e+01 +2.308930338548369576e+01 +1.141414496838892134e+01 +2.076859044007444766e+01 +1.099851300402323595e+01 +2.090351047163836640e+01 +2.054162743801968105e+01 +2.104040631225436542e+01 +1.522457801832482360e+01 +1.224775728390807394e+01 +1.749852458942579503e+01 +1.631939175545043597e+01 +2.439432608891361909e+01 +1.370747896471775995e+01 +2.389972310327109284e+01 +2.300082701059072221e+01 +2.575847034053987628e+01 +2.545767431183838525e+01 +1.898727575906286091e+01 +1.958841954206414115e+01 +1.369965517893767881e+01 +2.431441936521592595e+01 +1.895128879702857816e+01 +9.847456399540417848e+00 +1.181962740645215781e+01 +1.422040798395653560e+01 +1.428430603100776608e+01 +2.676149630719010730e+01 +2.297719676928022281e+01 +2.208252649014270830e+01 +1.243056000651459314e+01 +2.604574647049993175e+01 +1.076254308853040698e+01 +1.207405801608731366e+01 +1.750822680237399709e+01 +1.185069170150213758e+01 +1.590133621862598368e+01 +1.159540897018340644e+01 +1.125962091855839731e+01 +1.454326027012003131e+01 diff --git a/freezing_fritz/TurnUpTheHeat_Evaluation.ipynb b/freezing_fritz/TurnUpTheHeat_Evaluation.ipynb @@ -0,0 +1,3990 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib as mpl\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.pyplot import ion\n", + "from scipy.signal import convolve2d\n", + "import pandas as pd\n", + "import seaborn as sn\n", + "from sklearn.model_selection import train_test_split\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Freezing Fritz, is a pretty cool guy. He has one problem, though. In his house, it is quite often too cold or to hot during the night. Then he has to get up and open or close his windows or turn on the heat. Needless to say, he would like to avoid this. \n", + "\n", + "However, his flat has three doors that he can keep open or closed, it has four radiators, and four windows. It seems like there are endless possibilities of prepping the flat for whatever temperature the night will have. \n", + "\n", + "Fritz, does not want to play his luck any longer and decided to get active. He recorded the temperature outside and inside of his bedroom for the last two years. Now he would like to find an prediction that, given the outside temperature, as well as a certain configuration of his flat, tells him how cold or warm his bedroom will become.\n", + "\n", + "Can you help Freezing Fritz to find blissful sleep?\n", + "\n", + "\n", + "Let us first look at the situation. In the lecture notes you will find the experiment that Fritz carried out described in 8 cases." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For the experiment, we first load the data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>Window 1</th>\n", + " <th>Window 2</th>\n", + " <th>Window 3</th>\n", + " <th>Window 4</th>\n", + " <th>Heat Control 1</th>\n", + " <th>Heat Control 2</th>\n", + " <th>Heat Control 3</th>\n", + " <th>Heat Control 4</th>\n", + " 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"data_train_Temperature" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us look at this closely" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>Window 1</th>\n", + " <th>Window 2</th>\n", + " <th>Window 3</th>\n", + " <th>Window 4</th>\n", + " <th>Heat Control 1</th>\n", + " <th>Heat Control 2</th>\n", + " <th>Heat Control 3</th>\n", + " <th>Heat 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<th>max</th>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>5.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>1.000000</td>\n", + " <td>21.992202</td>\n", + " <td>33.882457</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " Window 1 Window 2 Window 3 Window 4 Heat Control 1 \\\n", + "count 1095.000000 1095.000000 1095.000000 1095.000000 1095.000000 \n", + "mean 0.515982 0.523288 0.519635 0.490411 2.518721 \n", + "std 0.499973 0.499686 0.499843 0.500136 1.716509 \n", + "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 0.000000 0.000000 0.000000 1.000000 \n", + "50% 1.000000 1.000000 1.000000 0.000000 3.000000 \n", + "75% 1.000000 1.000000 1.000000 1.000000 4.000000 \n", + "max 1.000000 1.000000 1.000000 1.000000 5.000000 \n", + "\n", + " Heat Control 2 Heat Control 3 Heat Control 4 Door 1 \\\n", + "count 1095.000000 1095.000000 1095.000000 1095.000000 \n", + "mean 2.463014 2.585388 2.528767 0.509589 \n", + "std 1.668685 1.702178 1.733328 0.500136 \n", + "min 0.000000 0.000000 0.000000 0.000000 \n", + "25% 1.000000 1.000000 1.000000 0.000000 \n", + "50% 2.000000 3.000000 2.000000 1.000000 \n", + "75% 4.000000 4.000000 4.000000 1.000000 \n", + "max 5.000000 5.000000 5.000000 1.000000 \n", + "\n", + " Door 2 Door 3 Temperature Outside Temperature Bed \n", + "count 1095.000000 1095.000000 1095.000000 1095.000000 \n", + "mean 0.499543 0.518721 8.572088 19.852056 \n", + "std 0.500228 0.499878 7.898873 6.926361 \n", + "min 0.000000 0.000000 -4.993865 0.590713 \n", + "25% 0.000000 0.000000 1.586682 14.603950 \n", + "50% 0.000000 1.000000 8.509676 20.950144 \n", + "75% 1.000000 1.000000 15.309044 25.284787 \n", + "max 1.000000 1.000000 21.992202 33.882457 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_train_Temperature.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We use the correlation matrix again to see how each of the parameters of the problem affect the temperature in the bedroom. We also look at how the trade-off between outside and inside temperature is affected by some of the parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 864x864 with 2 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "<Figure size 864x864 with 0 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 416.875x360 with 6 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 440.125x360 with 6 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 411.875x360 with 6 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "corrMatrix = data_train_Temperature.corr()\n", + "plt.figure(figsize = (12,12))\n", + "palette = sn.diverging_palette(20, 220, n=256)\n", + "sn.heatmap(corrMatrix, annot=False, cmap = palette, vmin = -1, vmax = 1)\n", + "plt.show()\n", + "\n", + "plt.figure(figsize = (12,12))\n", + "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Window 1')\n", + "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Heat Control 1')\n", + "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Door 1')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We do not have that many data points. We should therefore first reduce the dimensionality of the problem.\n", + "\n", + "My idea is to interpolate over the data but weigh it according to my observations. So I give low weights to windows 2 and 3. Same with door 3.\n", + "Then " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We predict on the first 80% of the data and then validate on the remaining 20%" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "observations = data_train_Temperature.shape[0]\n", + "simple_data_set = data_train_Temperature.copy().drop(range(int(0.2*observations)), axis = 0)\n", + "\n", + "def predict(data):\n", + " simple_test_set = data.copy()\n", + "\n", + " #some parameters are more important to fit right than others. (In our case, window 1 and doors 1 and 2)\n", + " weights = np.ones(12)\n", + " weights[0] = 10 # Window 1\n", + " weights[1] = 1 # Window 2\n", + " weights[2] = 1 # Window 3\n", + " weights[3] = 10 # Window 4\n", + " weights[4] = 1 # Heat 1\n", + " weights[5] = 1 # Heat 2\n", + " weights[6] = 1 # Heat 3\n", + " weights[7] = 0 # Heat 4\n", + " weights[8] = 10 # Door 1\n", + " weights[9] = 10 # Door 2\n", + " weights[10] = 1 # Door 3\n", + " weights[11] = 1 # Temp Out \n", + "\n", + " for k in range(simple_test_set.shape[0]):\n", + " value = 0;\n", + " totaldist = 0\n", + " \n", + " \n", + " for j in range(simple_data_set.values.shape[0]):\n", + " value = value + simple_data_set.values[j,-1]/(np.linalg.norm(weights*simple_data_set.values[j,:-1] - weights*simple_test_set.values[k,:-1]))**4\n", + " totaldist = totaldist + 1/(np.linalg.norm(weights*simple_data_set.values[j,:-1] - weights*simple_test_set.values[k,:-1]))**4\n", + " simple_test_set.values[k, -1] = np.max([value/totaldist, simple_data_set.values[j,-2]])\n", + " \n", + " \n", + " return simple_test_set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we compute error on validation set:" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3.25879966076991" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "validation_set = data_train_Temperature.copy().drop(range(int(0.2*observations), observations), axis = 0)\n", + "res = predict(validation_set)\n", + "# root mean square error:\n", + "np.linalg.norm(res.values[:,-1] - validation_set.values[:,-1])/np.sqrt(len(res.values[:,-1]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The algorithm, was not very sophisticated, nonetheless I came within an accuracy of 3.5 degrees. For me this seems acceptable. \n", + "Maybe you can help Freezing Fritz even more?\n", + "\n", + "I will just store my prediction on the test set now:" + ] + }, + { + "cell_type": "code", + "execution_count": 435, + "metadata": {}, + "outputs": [], + "source": [ + "#make prediction \n", + "prediction = predict(data_test_Temperature)\n", + "predicted_Temperatures = prediction.values[:,-1]\n", + " \n", + "np.savetxt('PhilippPetersens_Temperature_prediction.csv', predicted_Temperatures, delimiter=',') " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prediction" + ] + }, + { + "cell_type": "code", + "execution_count": 412, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.svm import SVR\n", + "from sklearn.svm import SVC\n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.pipeline import make_pipeline\n", + "from sklearn.model_selection import GridSearchCV\n", + "from sklearn.neural_network import MLPRegressor\n", + "\n", + "import keras\n", + "from keras.models import Sequential\n", + "from keras.layers import Dense, Activation" + ] + }, + { + "cell_type": "code", + "execution_count": 159, + "metadata": {}, + "outputs": [], + "source": [ + "X = data_train_Temperature.to_numpy()[:,:-1]\n", + "y = data_train_Temperature.to_numpy()[:,-1]\n", + "X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.20, random_state=42)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Support Vector Machine" + ] + }, + { + "cell_type": "code", + "execution_count": 269, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.8607722472011556" + ] + }, + "execution_count": 269, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "regr_svr = make_pipeline(StandardScaler(), SVR(C=1000, epsilon=0.45))\n", + "regr_svr.fit(X_train, y_train)\n", + "y_pred_svr = regr_svr.predict(X_valid)\n", + "np.linalg.norm(y_pred_svr-y_valid)/np.sqrt(len(y_valid))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Neural Network Regression" + ] + }, + { + "cell_type": "code", + "execution_count": 376, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.349415924948517" + ] + }, + "execution_count": 376, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "regr_nn = MLPRegressor(random_state=2,\\\n", + " max_iter=1300,\\\n", + " activation='relu')\n", + "regr_nn.fit(X_train, y_train)\n", + "y_pred_nn = regr_nn.predict(X_valid)\n", + "np.linalg.norm(y_pred_nn-y_valid)/np.sqrt(len(y_valid))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### With Keras" + ] + }, + { + "cell_type": "code", + "execution_count": 429, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 17.8158 - mse: 369.4533\n", + "Epoch 2/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 11.7027 - mse: 176.4969\n", + "Epoch 3/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 5.9129 - mse: 54.1465\n", + "Epoch 4/1400\n", + "28/28 [==============================] - 0s 2ms/step - loss: 4.9143 - mse: 37.7527\n", + "Epoch 5/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 4.7618 - mse: 36.9970\n", + "Epoch 6/1400\n", + "28/28 [==============================] - 0s 890us/step - loss: 4.6514 - mse: 36.0012\n", + "Epoch 7/1400\n", + "28/28 [==============================] - 0s 881us/step - loss: 4.5553 - mse: 35.2403\n", + "Epoch 8/1400\n", + "28/28 [==============================] - 0s 972us/step - loss: 4.4648 - mse: 34.3632\n", + "Epoch 9/1400\n", + "28/28 [==============================] - 0s 967us/step - loss: 4.3835 - mse: 33.2953\n", + "Epoch 10/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 4.3107 - mse: 32.1638\n", + "Epoch 11/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 4.2424 - mse: 31.7606\n", + "Epoch 12/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 4.1756 - mse: 30.9379\n", + "Epoch 13/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 4.1237 - mse: 30.2445\n", + "Epoch 14/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 4.0500 - mse: 29.2560\n", + "Epoch 15/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 3.9945 - mse: 28.4853\n", + "Epoch 16/1400\n", + "28/28 [==============================] - 0s 966us/step - loss: 3.9438 - mse: 28.0548\n", + "Epoch 17/1400\n", + "28/28 [==============================] - 0s 918us/step - loss: 3.8919 - mse: 27.3571\n", + "Epoch 18/1400\n", + "28/28 [==============================] - 0s 869us/step - loss: 3.8454 - mse: 26.6040\n", + "Epoch 19/1400\n", + "28/28 [==============================] - 0s 926us/step - loss: 3.7969 - mse: 25.9124\n", + "Epoch 20/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 3.7366 - mse: 25.4108\n", + "Epoch 21/1400\n", + "28/28 [==============================] - 0s 875us/step - loss: 3.6896 - mse: 24.6913\n", + "Epoch 22/1400\n", + "28/28 [==============================] - 0s 919us/step - loss: 3.6457 - mse: 23.5979\n", + "Epoch 23/1400\n", + "28/28 [==============================] - 0s 996us/step - loss: 3.6036 - mse: 23.5255\n", + "Epoch 24/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 3.5381 - mse: 22.9784\n", + "Epoch 25/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 3.5057 - mse: 22.1727\n", + "Epoch 26/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 3.4458 - mse: 21.4430\n", + "Epoch 27/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 3.4205 - mse: 21.1084\n", + "Epoch 28/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 3.3845 - mse: 20.5849\n", + "Epoch 29/1400\n", + "28/28 [==============================] - 0s 946us/step - loss: 3.3124 - mse: 19.9230\n", + "Epoch 30/1400\n", + "28/28 [==============================] - 0s 973us/step - loss: 3.2410 - mse: 18.8770\n", + "Epoch 31/1400\n", + "28/28 [==============================] - 0s 962us/step - loss: 3.2167 - mse: 18.8508\n", + "Epoch 32/1400\n", + "28/28 [==============================] - 0s 964us/step - loss: 3.1534 - mse: 18.0998\n", + "Epoch 33/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 3.0931 - mse: 17.5441\n", + "Epoch 34/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 3.0334 - mse: 16.8451\n", + "Epoch 35/1400\n", + "28/28 [==============================] - 0s 933us/step - loss: 2.9813 - mse: 16.2721\n", + "Epoch 36/1400\n", + "28/28 [==============================] - 0s 964us/step - loss: 2.9345 - mse: 15.8951\n", + "Epoch 37/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 2.8617 - mse: 15.1596\n", + "Epoch 38/1400\n", + "28/28 [==============================] - 0s 936us/step - loss: 2.8266 - mse: 14.9532\n", + "Epoch 39/1400\n", + "28/28 [==============================] - 0s 968us/step - loss: 2.7547 - mse: 14.2052\n", + "Epoch 40/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 2.6900 - mse: 13.6609\n", + "Epoch 41/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 2.6358 - mse: 13.1297\n", + "Epoch 42/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 2.6277 - mse: 12.8549\n", + "Epoch 43/1400\n", + "28/28 [==============================] - 0s 932us/step - loss: 2.5463 - mse: 12.1976\n", + "Epoch 44/1400\n", + "28/28 [==============================] - 0s 939us/step - loss: 2.4630 - mse: 11.6278\n", + "Epoch 45/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 2.3967 - mse: 11.1474\n", + "Epoch 46/1400\n", + "28/28 [==============================] - 0s 936us/step - loss: 2.3512 - mse: 10.8354\n", + "Epoch 47/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 2.3337 - mse: 10.3542\n", + "Epoch 48/1400\n", + "28/28 [==============================] - 0s 919us/step - loss: 2.2572 - mse: 10.1095\n", + "Epoch 49/1400\n", + "28/28 [==============================] - 0s 971us/step - loss: 2.2233 - mse: 9.6351\n", + "Epoch 50/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 2.1748 - mse: 9.5743\n", + "Epoch 51/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 2.1161 - mse: 8.9705\n", + "Epoch 52/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 2.0825 - mse: 8.8560\n", + "Epoch 53/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 2.0438 - mse: 8.3753\n", + "Epoch 54/1400\n", + "28/28 [==============================] - 0s 973us/step - loss: 1.9974 - 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6.3273\n", + "Epoch 64/1400\n", + "28/28 [==============================] - 0s 975us/step - loss: 1.7303 - mse: 6.2343\n", + "Epoch 65/1400\n", + "28/28 [==============================] - 0s 918us/step - loss: 1.7173 - mse: 6.1184\n", + "Epoch 66/1400\n", + "28/28 [==============================] - 0s 930us/step - loss: 1.6740 - mse: 5.8755\n", + "Epoch 67/1400\n", + "28/28 [==============================] - 0s 887us/step - loss: 1.6717 - mse: 5.8373\n", + "Epoch 68/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 1.6429 - mse: 5.5816\n", + "Epoch 69/1400\n", + "28/28 [==============================] - 0s 955us/step - loss: 1.6168 - mse: 5.4585\n", + "Epoch 70/1400\n", + "28/28 [==============================] - 0s 894us/step - loss: 1.6144 - mse: 5.3842\n", + "Epoch 71/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 1.6034 - mse: 5.1700\n", + "Epoch 72/1400\n", + "28/28 [==============================] - 0s 926us/step - loss: 1.6052 - mse: 5.2646\n", + "Epoch 73/1400\n", + "28/28 [==============================] - 0s 937us/step - loss: 1.5611 - mse: 4.9886\n", + "Epoch 74/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 1.5411 - mse: 4.8394\n", + "Epoch 75/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 1.5158 - mse: 4.6827\n", + "Epoch 76/1400\n", + "28/28 [==============================] - 0s 958us/step - loss: 1.5203 - mse: 4.7040\n", + "Epoch 77/1400\n", + "28/28 [==============================] - 0s 975us/step - loss: 1.4923 - mse: 4.5807\n", + "Epoch 78/1400\n", + "28/28 [==============================] - 0s 888us/step - loss: 1.4785 - mse: 4.4374\n", + "Epoch 79/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 1.4715 - mse: 4.3557\n", + "Epoch 80/1400\n", + "28/28 [==============================] - 0s 922us/step - loss: 1.4386 - mse: 4.2619\n", + "Epoch 81/1400\n", + "28/28 [==============================] - 0s 893us/step - loss: 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90/1400\n", + "28/28 [==============================] - 0s 866us/step - loss: 1.3026 - mse: 3.4339\n", + "Epoch 91/1400\n", + "28/28 [==============================] - 0s 882us/step - loss: 1.2947 - mse: 3.3892\n", + "Epoch 92/1400\n", + "28/28 [==============================] - 0s 867us/step - loss: 1.3001 - mse: 3.4023\n", + "Epoch 93/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 1.2726 - mse: 3.2662\n", + "Epoch 94/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 1.2569 - mse: 3.2291\n", + "Epoch 95/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 1.2651 - mse: 3.2244\n", + "Epoch 96/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 1.2280 - mse: 3.1128\n", + "Epoch 97/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 1.2198 - mse: 3.0833\n", + "Epoch 98/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 1.2104 - mse: 3.0272\n", + "Epoch 99/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 1.2791 - mse: 3.2320\n", + "Epoch 100/1400\n", + "28/28 [==============================] - 0s 951us/step - loss: 1.2620 - mse: 3.1578\n", + "Epoch 101/1400\n", + "28/28 [==============================] - 0s 923us/step - loss: 1.2178 - mse: 2.9291\n", + "Epoch 102/1400\n", + "28/28 [==============================] - 0s 979us/step - loss: 1.1791 - mse: 2.8952\n", + "Epoch 103/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 1.1708 - mse: 2.8452\n", + "Epoch 104/1400\n", + "28/28 [==============================] - 0s 955us/step - loss: 1.1710 - mse: 2.8170\n", + "Epoch 105/1400\n", + "28/28 [==============================] - 0s 917us/step - loss: 1.1472 - mse: 2.7237\n", + "Epoch 106/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 1.1383 - mse: 2.6730\n", + "Epoch 107/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 1.1435 - mse: 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938us/step - loss: 0.7060 - mse: 1.1628\n", + "Epoch 240/1400\n", + "28/28 [==============================] - 0s 934us/step - loss: 0.7192 - mse: 1.1833\n", + "Epoch 241/1400\n", + "28/28 [==============================] - 0s 989us/step - loss: 0.7291 - mse: 1.1959\n", + "Epoch 242/1400\n", + "28/28 [==============================] - 0s 940us/step - loss: 0.7016 - mse: 1.1360\n", + "Epoch 243/1400\n", + "28/28 [==============================] - 0s 946us/step - loss: 0.6849 - mse: 1.1129\n", + "Epoch 244/1400\n", + "28/28 [==============================] - 0s 993us/step - loss: 0.7072 - mse: 1.1498\n", + "Epoch 245/1400\n", + "28/28 [==============================] - 0s 970us/step - loss: 0.6939 - mse: 1.1204\n", + "Epoch 246/1400\n", + "28/28 [==============================] - 0s 889us/step - loss: 0.7056 - mse: 1.1537\n", + "Epoch 247/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 0.7097 - mse: 1.1380\n", + "Epoch 248/1400\n", + "28/28 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1ms/step - loss: 0.6320 - mse: 1.0085\n", + "Epoch 292/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 0.6561 - mse: 1.0373\n", + "Epoch 293/1400\n", + "28/28 [==============================] - 0s 883us/step - loss: 0.6346 - mse: 0.9860\n", + "Epoch 294/1400\n", + "28/28 [==============================] - 0s 918us/step - loss: 0.6450 - mse: 1.0161\n", + "Epoch 295/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6487 - mse: 1.0083\n", + "Epoch 296/1400\n", + "28/28 [==============================] - 0s 980us/step - loss: 0.6457 - mse: 1.0228\n", + "Epoch 297/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.6382 - mse: 1.0126\n", + "Epoch 298/1400\n", + "28/28 [==============================] - 0s 864us/step - loss: 0.6233 - mse: 0.9784\n", + "Epoch 299/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6387 - mse: 1.0113\n", + "Epoch 300/1400\n", + "28/28 [==============================] - 0s 923us/step - loss: 0.6143 - mse: 0.9564\n", + "Epoch 301/1400\n", + "28/28 [==============================] - 0s 871us/step - loss: 0.6267 - mse: 0.9805\n", + "Epoch 302/1400\n", + "28/28 [==============================] - 0s 974us/step - loss: 0.6222 - mse: 0.9652\n", + "Epoch 303/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6388 - mse: 1.0017\n", + "Epoch 304/1400\n", + "28/28 [==============================] - 0s 947us/step - loss: 0.6375 - mse: 0.9849\n", + "Epoch 305/1400\n", + "28/28 [==============================] - 0s 871us/step - loss: 0.6170 - mse: 0.9567\n", + "Epoch 306/1400\n", + "28/28 [==============================] - 0s 922us/step - loss: 0.6215 - mse: 0.9747\n", + "Epoch 307/1400\n", + "28/28 [==============================] - 0s 979us/step - loss: 0.6205 - mse: 0.9725\n", + "Epoch 308/1400\n", + "28/28 [==============================] - 0s 909us/step - loss: 0.6606 - mse: 1.0157\n", + "Epoch 309/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.6776 - mse: 1.0317\n", + "Epoch 310/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 0.6103 - mse: 0.9409\n", + "Epoch 311/1400\n", + "28/28 [==============================] - 0s 952us/step - loss: 0.6256 - mse: 0.9741\n", + "Epoch 312/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 0.6173 - mse: 0.9466\n", + "Epoch 313/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.6078 - mse: 0.9423\n", + "Epoch 314/1400\n", + "28/28 [==============================] - 0s 922us/step - loss: 0.6055 - mse: 0.9346\n", + "Epoch 315/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.6237 - mse: 0.9655\n", + "Epoch 316/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6126 - mse: 0.9372\n", + "Epoch 317/1400\n", + "28/28 [==============================] - 0s 945us/step - loss: 0.5972 - mse: 0.9207\n", + "Epoch 318/1400\n", + "28/28 [==============================] - 0s 877us/step - loss: 0.6041 - mse: 0.9542\n", + "Epoch 319/1400\n", + "28/28 [==============================] - 0s 968us/step - loss: 0.6052 - mse: 0.9311\n", + "Epoch 320/1400\n", + "28/28 [==============================] - 0s 981us/step - loss: 0.5974 - mse: 0.9225\n", + "Epoch 321/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6008 - mse: 0.9323\n", + "Epoch 322/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6213 - mse: 0.9565\n", + "Epoch 323/1400\n", + "28/28 [==============================] - 0s 948us/step - loss: 0.6241 - mse: 0.9407\n", + "Epoch 324/1400\n", + "28/28 [==============================] - 0s 881us/step - loss: 0.6166 - mse: 0.9562\n", + "Epoch 325/1400\n", + "28/28 [==============================] - 0s 947us/step - loss: 0.6248 - mse: 0.9392\n", + "Epoch 326/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6247 - mse: 0.9566\n", + "Epoch 327/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.6090 - mse: 0.9228\n", + "Epoch 328/1400\n", + "28/28 [==============================] - 0s 860us/step - loss: 0.6242 - mse: 0.9545\n", + "Epoch 329/1400\n", + "28/28 [==============================] - 0s 939us/step - loss: 0.6149 - mse: 0.9128\n", + "Epoch 330/1400\n", + "28/28 [==============================] - 0s 926us/step - loss: 0.5975 - mse: 0.9127\n", + "Epoch 331/1400\n", + "28/28 [==============================] - 0s 911us/step - loss: 0.5898 - mse: 0.8975\n", + "Epoch 332/1400\n", + "28/28 [==============================] - 0s 946us/step - loss: 0.6118 - mse: 0.9240\n", + "Epoch 333/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 2ms/step - loss: 0.6013 - mse: 0.9075\n", + "Epoch 334/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 0.5760 - mse: 0.8848\n", + "Epoch 335/1400\n", + "28/28 [==============================] - 0s 892us/step - loss: 0.5895 - mse: 0.8988\n", + "Epoch 336/1400\n", + "28/28 [==============================] - 0s 959us/step - loss: 0.5882 - mse: 0.8945\n", + "Epoch 337/1400\n", + "28/28 [==============================] - 0s 963us/step - loss: 0.5833 - mse: 0.8912\n", + "Epoch 338/1400\n", + "28/28 [==============================] - 0s 850us/step - loss: 0.6050 - mse: 0.9297\n", + "Epoch 339/1400\n", + "28/28 [==============================] - 0s 891us/step - loss: 0.6103 - mse: 0.9219\n", + "Epoch 340/1400\n", + "28/28 [==============================] - 0s 980us/step - loss: 0.5772 - mse: 0.8859\n", + "Epoch 341/1400\n", + "28/28 [==============================] - 0s 873us/step - loss: 0.5842 - mse: 0.8838\n", + "Epoch 342/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.6098 - mse: 0.9214\n", + "Epoch 343/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.5828 - 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- loss: 0.5817 - mse: 0.8583\n", + "Epoch 353/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5905 - mse: 0.8722\n", + "Epoch 354/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5752 - mse: 0.8572\n", + "Epoch 355/1400\n", + "28/28 [==============================] - 0s 872us/step - loss: 0.5813 - mse: 0.8627\n", + "Epoch 356/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.5752 - mse: 0.8558\n", + "Epoch 357/1400\n", + "28/28 [==============================] - 0s 855us/step - loss: 0.5631 - mse: 0.8281\n", + "Epoch 358/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5670 - mse: 0.8454\n", + "Epoch 359/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5824 - mse: 0.8671\n", + "Epoch 360/1400\n", + "28/28 [==============================] - 0s 867us/step - loss: 0.5913 - mse: 0.8695\n", + "Epoch 361/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.5706 - mse: 0.8565\n", + "Epoch 362/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.6052 - mse: 0.8946\n", + "Epoch 363/1400\n", + "28/28 [==============================] - 0s 932us/step - loss: 0.5897 - mse: 0.8776\n", + "Epoch 364/1400\n", + "28/28 [==============================] - 0s 922us/step - loss: 0.5650 - mse: 0.8343\n", + "Epoch 365/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5758 - mse: 0.8250\n", + "Epoch 366/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 0.5553 - mse: 0.8208\n", + "Epoch 367/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.5628 - mse: 0.8296\n", + "Epoch 368/1400\n", + "28/28 [==============================] - 0s 965us/step - loss: 0.5942 - mse: 0.8729\n", + "Epoch 369/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5645 - mse: 0.8340\n", + "Epoch 370/1400\n", + "28/28 [==============================] - 0s 933us/step - loss: 0.5820 - mse: 0.8555\n", + "Epoch 371/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 0.5885 - mse: 0.8366\n", + "Epoch 372/1400\n", + "28/28 [==============================] - 0s 938us/step - loss: 0.5748 - mse: 0.8419\n", + "Epoch 373/1400\n", + "28/28 [==============================] - 0s 962us/step - loss: 0.5695 - mse: 0.8231\n", + "Epoch 374/1400\n", + "28/28 [==============================] - 0s 923us/step - loss: 0.6046 - mse: 0.8563\n", + "Epoch 375/1400\n", + "28/28 [==============================] - 0s 869us/step - loss: 0.5675 - mse: 0.8337\n", + "Epoch 376/1400\n", + "28/28 [==============================] - 0s 990us/step - loss: 0.5503 - mse: 0.8065\n", + "Epoch 377/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.5646 - mse: 0.8192\n", + "Epoch 378/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.5615 - mse: 0.8167\n", + "Epoch 379/1400\n", + "28/28 [==============================] - 0s 940us/step - loss: 0.5600 - mse: 0.8119\n", + "Epoch 380/1400\n", + "28/28 [==============================] - 0s 901us/step - loss: 0.5571 - mse: 0.8109\n", + "Epoch 381/1400\n", + "28/28 [==============================] - 0s 866us/step - loss: 0.5545 - mse: 0.8063\n", + "Epoch 382/1400\n", + "28/28 [==============================] - 0s 970us/step - loss: 0.5529 - mse: 0.8144\n", + "Epoch 383/1400\n", + "28/28 [==============================] - 0s 936us/step - loss: 0.5539 - mse: 0.8056\n", + "Epoch 384/1400\n", + "28/28 [==============================] - 0s 900us/step - loss: 0.5536 - mse: 0.8107\n", + "Epoch 385/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5459 - mse: 0.8017\n", + "Epoch 386/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5454 - mse: 0.7968\n", + "Epoch 387/1400\n", + "28/28 [==============================] - 0s 894us/step - loss: 0.5476 - mse: 0.8004\n", + "Epoch 388/1400\n", + "28/28 [==============================] - 0s 971us/step - loss: 0.5633 - mse: 0.8150\n", + "Epoch 389/1400\n", + "28/28 [==============================] - 0s 973us/step - loss: 0.5538 - mse: 0.8120\n", + "Epoch 390/1400\n", + "28/28 [==============================] - 0s 953us/step - loss: 0.6197 - mse: 0.8829\n", + "Epoch 391/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.5919 - mse: 0.8247\n", + "Epoch 392/1400\n", + "28/28 [==============================] - 0s 875us/step - loss: 0.5652 - mse: 0.8190\n", + "Epoch 393/1400\n", + "28/28 [==============================] - 0s 901us/step - loss: 0.5666 - mse: 0.8121\n", + "Epoch 394/1400\n", + "28/28 [==============================] - 0s 930us/step - loss: 0.5625 - mse: 0.7888\n", + "Epoch 395/1400\n", + "28/28 [==============================] - 0s 982us/step - loss: 0.5501 - mse: 0.8000\n", + "Epoch 396/1400\n", + "28/28 [==============================] - 0s 888us/step - 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[==============================] - 0s 953us/step - loss: 0.5573 - mse: 0.7804\n", + "Epoch 415/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.5528 - mse: 0.7836\n", + "Epoch 416/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 924us/step - loss: 0.5403 - mse: 0.7586\n", + "Epoch 417/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 0.5449 - mse: 0.7680\n", + "Epoch 418/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.5536 - mse: 0.7880\n", + "Epoch 419/1400\n", + "28/28 [==============================] - 0s 988us/step - loss: 0.5398 - mse: 0.7622\n", + "Epoch 420/1400\n", + "28/28 [==============================] - 0s 946us/step - loss: 0.5325 - mse: 0.7548\n", + "Epoch 421/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.5218 - mse: 0.7525\n", + "Epoch 422/1400\n", + "28/28 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431/1400\n", + "28/28 [==============================] - 0s 969us/step - loss: 0.5555 - mse: 0.7791\n", + "Epoch 432/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.5574 - mse: 0.7765\n", + "Epoch 433/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 0.5392 - mse: 0.7541\n", + "Epoch 434/1400\n", + "28/28 [==============================] - 0s 922us/step - loss: 0.5268 - mse: 0.7492\n", + "Epoch 435/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 0.5212 - mse: 0.7293\n", + "Epoch 436/1400\n", + "28/28 [==============================] - 0s 951us/step - loss: 0.5297 - mse: 0.7434\n", + "Epoch 437/1400\n", + "28/28 [==============================] - 0s 901us/step - loss: 0.5255 - mse: 0.7362\n", + "Epoch 438/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.5143 - mse: 0.7312\n", + "Epoch 439/1400\n", + "28/28 [==============================] - 0s 893us/step - loss: 0.5187 - mse: 0.7380\n", + "Epoch 440/1400\n", + "28/28 [==============================] - 0s 892us/step - loss: 0.5504 - mse: 0.7765\n", + "Epoch 441/1400\n", + "28/28 [==============================] - 0s 918us/step - loss: 0.5239 - mse: 0.7294\n", + "Epoch 442/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5386 - mse: 0.7423\n", + "Epoch 443/1400\n", + "28/28 [==============================] - 0s 889us/step - loss: 0.5355 - mse: 0.7541\n", + "Epoch 444/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 0.5382 - mse: 0.7408\n", + "Epoch 445/1400\n", + "28/28 [==============================] - 0s 907us/step - loss: 0.5265 - mse: 0.7428\n", + "Epoch 446/1400\n", + "28/28 [==============================] - 0s 976us/step - loss: 0.5624 - mse: 0.7697\n", + "Epoch 447/1400\n", + "28/28 [==============================] - 0s 981us/step - loss: 0.5753 - mse: 0.7968\n", + "Epoch 448/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 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909us/step - loss: 0.5473 - mse: 0.7507\n", + "Epoch 458/1400\n", + "28/28 [==============================] - 0s 968us/step - loss: 0.5131 - mse: 0.7113\n", + "Epoch 459/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.5091 - mse: 0.7135\n", + "Epoch 460/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 0.5009 - mse: 0.7024\n", + "Epoch 461/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.5193 - mse: 0.7176\n", + "Epoch 462/1400\n", + "28/28 [==============================] - 0s 967us/step - loss: 0.5185 - mse: 0.7112\n", + "Epoch 463/1400\n", + "28/28 [==============================] - 0s 996us/step - loss: 0.5292 - mse: 0.7349\n", + "Epoch 464/1400\n", + "28/28 [==============================] - 0s 905us/step - loss: 0.5421 - mse: 0.7322\n", + "Epoch 465/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.5532 - mse: 0.7504\n", + "Epoch 466/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.5108 - mse: 0.7121\n", + "Epoch 467/1400\n", + "28/28 [==============================] - 0s 973us/step - loss: 0.5458 - mse: 0.7499\n", + "Epoch 468/1400\n", + "28/28 [==============================] - 0s 878us/step - loss: 0.5436 - mse: 0.7427\n", + "Epoch 469/1400\n", + "28/28 [==============================] - 0s 918us/step - loss: 0.5267 - mse: 0.7159\n", + "Epoch 470/1400\n", + "28/28 [==============================] - 0s 940us/step - loss: 0.5433 - mse: 0.7272\n", + "Epoch 471/1400\n", + "28/28 [==============================] - 0s 888us/step - loss: 0.5222 - mse: 0.7128\n", + "Epoch 472/1400\n", + "28/28 [==============================] - 0s 930us/step - loss: 0.5154 - mse: 0.6977\n", + "Epoch 473/1400\n", + "28/28 [==============================] - 0s 918us/step - loss: 0.5404 - mse: 0.7370\n", + "Epoch 474/1400\n", + "28/28 [==============================] - 0s 957us/step - loss: 0.5032 - mse: 0.6944\n", + "Epoch 475/1400\n", + "28/28 [==============================] - 0s 955us/step - loss: 0.5043 - mse: 0.6900\n", + "Epoch 476/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4978 - mse: 0.6871\n", + "Epoch 477/1400\n", + "28/28 [==============================] - 0s 905us/step - loss: 0.5123 - mse: 0.6977\n", + "Epoch 478/1400\n", + "28/28 [==============================] - 0s 958us/step - loss: 0.5006 - mse: 0.6868\n", + "Epoch 479/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 0.5439 - mse: 0.7281\n", + "Epoch 480/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.5167 - mse: 0.7022\n", + "Epoch 481/1400\n", + "28/28 [==============================] - 0s 987us/step - loss: 0.5186 - mse: 0.7101\n", + "Epoch 482/1400\n", + "28/28 [==============================] - 0s 906us/step - loss: 0.5160 - mse: 0.7042\n", + "Epoch 483/1400\n", + "28/28 [==============================] - 0s 906us/step - loss: 0.4945 - mse: 0.6717\n", + "Epoch 484/1400\n", + "28/28 [==============================] - 0s 855us/step - loss: 0.4920 - mse: 0.6728\n", + "Epoch 485/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 0.4973 - mse: 0.6882\n", + "Epoch 486/1400\n", + "28/28 [==============================] - 0s 925us/step - loss: 0.5181 - mse: 0.6973\n", + "Epoch 487/1400\n", + "28/28 [==============================] - 0s 974us/step - loss: 0.5020 - mse: 0.6849\n", + "Epoch 488/1400\n", + "28/28 [==============================] - 0s 945us/step - loss: 0.5037 - mse: 0.6943\n", + "Epoch 489/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 0.4932 - mse: 0.6760\n", + "Epoch 490/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.5058 - mse: 0.7005\n", + "Epoch 491/1400\n", + "28/28 [==============================] - 0s 864us/step - loss: 0.5095 - mse: 0.7003\n", + "Epoch 492/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4939 - mse: 0.6717\n", + "Epoch 493/1400\n", + "28/28 [==============================] - 0s 916us/step - loss: 0.4937 - mse: 0.6803\n", + "Epoch 494/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4955 - mse: 0.6762\n", + "Epoch 495/1400\n", + "28/28 [==============================] - 0s 940us/step - loss: 0.4816 - mse: 0.6614\n", + "Epoch 496/1400\n", + "28/28 [==============================] - 0s 980us/step - loss: 0.4845 - mse: 0.6670\n", + "Epoch 497/1400\n", + "28/28 [==============================] - 0s 926us/step - loss: 0.4952 - mse: 0.6698\n", + "Epoch 498/1400\n", + "28/28 [==============================] - 0s 886us/step - loss: 0.5239 - mse: 0.6916\n", + "Epoch 499/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 966us/step - loss: 0.5273 - mse: 0.7062\n", + "Epoch 500/1400\n", + "28/28 [==============================] - 0s 894us/step - loss: 0.5061 - mse: 0.6828\n", + "Epoch 501/1400\n", + "28/28 [==============================] - 0s 880us/step - loss: 0.5047 - mse: 0.6695\n", + "Epoch 502/1400\n", + "28/28 [==============================] - 0s 997us/step - loss: 0.4925 - mse: 0.6653\n", + "Epoch 503/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.4879 - mse: 0.6576\n", + "Epoch 504/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 0.4923 - mse: 0.6694\n", + "Epoch 505/1400\n", + "28/28 [==============================] - 0s 895us/step - loss: 0.5010 - mse: 0.6716\n", + "Epoch 506/1400\n", + "28/28 [==============================] - 0s 985us/step - loss: 0.4959 - mse: 0.6654\n", + "Epoch 507/1400\n", + "28/28 [==============================] - 0s 949us/step - loss: 0.5044 - mse: 0.6641\n", + "Epoch 508/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.5267 - mse: 0.7025\n", + "Epoch 509/1400\n", + "28/28 [==============================] - 0s 959us/step - loss: 0.5291 - mse: 0.7110\n", + "Epoch 510/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.4865 - mse: 0.6499\n", + "Epoch 511/1400\n", + "28/28 [==============================] - 0s 983us/step - loss: 0.4942 - mse: 0.6689\n", + "Epoch 512/1400\n", + "28/28 [==============================] - 0s 903us/step - loss: 0.4898 - mse: 0.6639\n", + "Epoch 513/1400\n", + "28/28 [==============================] - 0s 971us/step - loss: 0.4898 - mse: 0.6548\n", + "Epoch 514/1400\n", + "28/28 [==============================] - 0s 900us/step - loss: 0.5101 - mse: 0.6616\n", + "Epoch 515/1400\n", + "28/28 [==============================] - 0s 2ms/step - loss: 0.5283 - mse: 0.7014\n", + "Epoch 516/1400\n", + "28/28 [==============================] - 0s 964us/step - loss: 0.5374 - mse: 0.6886\n", + "Epoch 517/1400\n", + "28/28 [==============================] - 0s 949us/step - loss: 0.4899 - mse: 0.6536\n", + "Epoch 518/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.5203 - mse: 0.6758\n", + "Epoch 519/1400\n", + "28/28 [==============================] - 0s 913us/step - loss: 0.4969 - mse: 0.6610\n", + "Epoch 520/1400\n", + "28/28 [==============================] - 0s 966us/step - loss: 0.4876 - mse: 0.6535\n", + "Epoch 521/1400\n", + "28/28 [==============================] - 0s 940us/step - loss: 0.4948 - mse: 0.6609\n", + "Epoch 522/1400\n", + "28/28 [==============================] - 0s 906us/step - loss: 0.5004 - mse: 0.6603\n", + "Epoch 523/1400\n", + "28/28 [==============================] - 0s 948us/step - loss: 0.5082 - mse: 0.6659\n", + "Epoch 524/1400\n", + "28/28 [==============================] - 0s 970us/step - loss: 0.5023 - mse: 0.6724\n", + "Epoch 525/1400\n", + "28/28 [==============================] - 0s 890us/step - loss: 0.4933 - mse: 0.6504\n", + "Epoch 526/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.4946 - mse: 0.6441\n", + "Epoch 527/1400\n", + "28/28 [==============================] - 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[==============================] - 0s 893us/step - loss: 0.4861 - mse: 0.6437\n", + "Epoch 537/1400\n", + "28/28 [==============================] - 0s 907us/step - loss: 0.4736 - mse: 0.6271\n", + "Epoch 538/1400\n", + "28/28 [==============================] - 0s 877us/step - loss: 0.5001 - mse: 0.6588\n", + "Epoch 539/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4678 - mse: 0.6311\n", + "Epoch 540/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4747 - mse: 0.6461\n", + "Epoch 541/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.4724 - mse: 0.6382\n", + "Epoch 542/1400\n", + "28/28 [==============================] - 0s 969us/step - loss: 0.4944 - mse: 0.6502\n", + "Epoch 543/1400\n", + "28/28 [==============================] - 0s 951us/step - loss: 0.4754 - mse: 0.6313\n", + "Epoch 544/1400\n", + "28/28 [==============================] - 0s 891us/step - loss: 0.4635 - mse: 0.6240\n", + "Epoch 545/1400\n", + "28/28 [==============================] - 0s 969us/step - loss: 0.4754 - mse: 0.6221\n", + "Epoch 546/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4670 - mse: 0.6232\n", + "Epoch 547/1400\n", + "28/28 [==============================] - 0s 923us/step - loss: 0.4818 - mse: 0.6341\n", + "Epoch 548/1400\n", + "28/28 [==============================] - 0s 868us/step - loss: 0.4804 - mse: 0.6398\n", + "Epoch 549/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.4873 - mse: 0.6341\n", + "Epoch 550/1400\n", + "28/28 [==============================] - 0s 882us/step - loss: 0.4824 - mse: 0.6347\n", + "Epoch 551/1400\n", + "28/28 [==============================] - 0s 916us/step - loss: 0.4707 - mse: 0.6236\n", + "Epoch 552/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4704 - mse: 0.6272\n", + "Epoch 553/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4713 - mse: 0.6215\n", + "Epoch 554/1400\n", + "28/28 [==============================] - 0s 879us/step - loss: 0.5044 - mse: 0.6432\n", + "Epoch 555/1400\n", + "28/28 [==============================] - 0s 889us/step - loss: 0.4991 - mse: 0.6497\n", + "Epoch 556/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.5137 - mse: 0.6491\n", + "Epoch 557/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4900 - mse: 0.6452\n", + "Epoch 558/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.4614 - mse: 0.6164\n", + "Epoch 559/1400\n", + "28/28 [==============================] - 0s 886us/step - loss: 0.4729 - mse: 0.6130\n", + "Epoch 560/1400\n", + "28/28 [==============================] - 0s 959us/step - loss: 0.4815 - mse: 0.6266\n", + "Epoch 561/1400\n", + "28/28 [==============================] - 0s 902us/step - loss: 0.4902 - mse: 0.6347\n", + "Epoch 562/1400\n", + "28/28 [==============================] - 0s 897us/step - loss: 0.4713 - mse: 0.6263\n", + "Epoch 563/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4608 - mse: 0.6066\n", + "Epoch 564/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4725 - mse: 0.6212\n", + "Epoch 565/1400\n", + "28/28 [==============================] - 0s 949us/step - loss: 0.4683 - mse: 0.6167\n", + "Epoch 566/1400\n", + "28/28 [==============================] - 0s 856us/step - loss: 0.4709 - mse: 0.6292\n", + "Epoch 567/1400\n", + "28/28 [==============================] - 0s 916us/step - loss: 0.4657 - mse: 0.6168\n", + "Epoch 568/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4987 - mse: 0.6372\n", + "Epoch 569/1400\n", + "28/28 [==============================] - 0s 897us/step - loss: 0.5377 - mse: 0.6868\n", + "Epoch 570/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.5071 - mse: 0.6501\n", + "Epoch 571/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.5062 - mse: 0.6435\n", + "Epoch 572/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.4730 - mse: 0.6166\n", + "Epoch 573/1400\n", + "28/28 [==============================] - 0s 932us/step - loss: 0.4675 - mse: 0.6101\n", + "Epoch 574/1400\n", + "28/28 [==============================] - 0s 945us/step - loss: 0.4787 - mse: 0.6219\n", + "Epoch 575/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.5047 - mse: 0.6448\n", + "Epoch 576/1400\n", + "28/28 [==============================] - 0s 945us/step - loss: 0.4654 - mse: 0.6067\n", + "Epoch 577/1400\n", + "28/28 [==============================] - 0s 882us/step - loss: 0.4795 - mse: 0.6196\n", + "Epoch 578/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.4832 - mse: 0.6292\n", + "Epoch 579/1400\n", + "28/28 [==============================] - 0s 902us/step - loss: 0.4698 - mse: 0.6137\n", + "Epoch 580/1400\n", + "28/28 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+ "Epoch 833/1400\n", + "28/28 [==============================] - 0s 857us/step - loss: 0.4009 - mse: 0.4416\n", + "Epoch 834/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3894 - mse: 0.4433\n", + "Epoch 835/1400\n", + "28/28 [==============================] - 0s 879us/step - loss: 0.3980 - mse: 0.4450\n", + "Epoch 836/1400\n", + "28/28 [==============================] - 0s 888us/step - loss: 0.3891 - mse: 0.4270\n", + "Epoch 837/1400\n", + "28/28 [==============================] - 0s 979us/step - loss: 0.3914 - mse: 0.4388\n", + "Epoch 838/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3977 - mse: 0.4394\n", + "Epoch 839/1400\n", + "28/28 [==============================] - 0s 888us/step - loss: 0.4096 - mse: 0.4425\n", + "Epoch 840/1400\n", + "28/28 [==============================] - 0s 897us/step - loss: 0.4008 - mse: 0.4438\n", + "Epoch 841/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3995 - mse: 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1ms/step - loss: 0.3780 - mse: 0.4162\n", + "Epoch 913/1400\n", + "28/28 [==============================] - 0s 975us/step - loss: 0.3782 - mse: 0.4003\n", + "Epoch 914/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 948us/step - loss: 0.3969 - mse: 0.4186\n", + "Epoch 915/1400\n", + "28/28 [==============================] - 0s 973us/step - loss: 0.4033 - mse: 0.4267\n", + "Epoch 916/1400\n", + "28/28 [==============================] - 0s 919us/step - loss: 0.3879 - mse: 0.4131\n", + "Epoch 917/1400\n", + "28/28 [==============================] - 0s 902us/step - loss: 0.3904 - mse: 0.4156\n", + "Epoch 918/1400\n", + "28/28 [==============================] - 0s 871us/step - loss: 0.3902 - mse: 0.4144\n", + "Epoch 919/1400\n", + "28/28 [==============================] - 0s 975us/step - loss: 0.3837 - mse: 0.4134\n", + "Epoch 920/1400\n", + "28/28 [==============================] - 0s 984us/step - loss: 0.3850 - mse: 0.4105\n", + "Epoch 921/1400\n", + "28/28 [==============================] - 0s 865us/step - loss: 0.4145 - mse: 0.4324\n", + "Epoch 922/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.3828 - mse: 0.4017\n", + "Epoch 923/1400\n", + "28/28 [==============================] - 0s 859us/step - loss: 0.3846 - mse: 0.4081\n", + "Epoch 924/1400\n", + "28/28 [==============================] - 0s 941us/step - loss: 0.3916 - mse: 0.4148\n", + "Epoch 925/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.3785 - mse: 0.4106\n", + "Epoch 926/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 0.3743 - mse: 0.4017\n", + "Epoch 927/1400\n", + "28/28 [==============================] - 0s 865us/step - loss: 0.3925 - mse: 0.4127\n", + "Epoch 928/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3863 - mse: 0.4100\n", + "Epoch 929/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 0.3975 - mse: 0.4211\n", + "Epoch 930/1400\n", + "28/28 [==============================] - 0s 912us/step - loss: 0.4066 - mse: 0.4288\n", + "Epoch 931/1400\n", + "28/28 [==============================] - 0s 860us/step - loss: 0.3748 - mse: 0.4026\n", + "Epoch 932/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.4004 - mse: 0.4190\n", + "Epoch 933/1400\n", + "28/28 [==============================] - 0s 992us/step - loss: 0.3828 - mse: 0.4111\n", + "Epoch 934/1400\n", + "28/28 [==============================] - 0s 932us/step - loss: 0.3741 - mse: 0.4016\n", + "Epoch 935/1400\n", + "28/28 [==============================] - 0s 930us/step - loss: 0.3709 - mse: 0.4045\n", + "Epoch 936/1400\n", + "28/28 [==============================] - 0s 874us/step - loss: 0.3916 - mse: 0.4165\n", + "Epoch 937/1400\n", + "28/28 [==============================] - 0s 887us/step - loss: 0.3907 - mse: 0.4086\n", + "Epoch 938/1400\n", + "28/28 [==============================] - 0s 974us/step - loss: 0.3796 - mse: 0.3966\n", + "Epoch 939/1400\n", + "28/28 [==============================] - 0s 982us/step - loss: 0.3892 - mse: 0.4089\n", + "Epoch 940/1400\n", + "28/28 [==============================] - 0s 863us/step - loss: 0.4153 - mse: 0.4305\n", + "Epoch 941/1400\n", + "28/28 [==============================] - 0s 886us/step - loss: 0.4200 - mse: 0.4353\n", + "Epoch 942/1400\n", + "28/28 [==============================] - 0s 954us/step - loss: 0.4030 - mse: 0.4176\n", + "Epoch 943/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.3792 - mse: 0.4022\n", + "Epoch 944/1400\n", + "28/28 [==============================] - 0s 897us/step - loss: 0.3738 - mse: 0.4008\n", + "Epoch 945/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3715 - mse: 0.3982\n", + "Epoch 946/1400\n", + "28/28 [==============================] - 0s 880us/step - loss: 0.3810 - mse: 0.3988\n", + "Epoch 947/1400\n", + "28/28 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956/1400\n", + "28/28 [==============================] - 0s 925us/step - loss: 0.3847 - mse: 0.3987\n", + "Epoch 957/1400\n", + "28/28 [==============================] - 0s 999us/step - loss: 0.3943 - mse: 0.4151\n", + "Epoch 958/1400\n", + "28/28 [==============================] - 0s 938us/step - loss: 0.3909 - mse: 0.4021\n", + "Epoch 959/1400\n", + "28/28 [==============================] - 0s 877us/step - loss: 0.4230 - mse: 0.4356\n", + "Epoch 960/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 0.3884 - mse: 0.3994\n", + "Epoch 961/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3682 - mse: 0.3885\n", + "Epoch 962/1400\n", + "28/28 [==============================] - 0s 874us/step - loss: 0.3648 - mse: 0.3911\n", + "Epoch 963/1400\n", + "28/28 [==============================] - 0s 901us/step - loss: 0.3733 - mse: 0.3909\n", + "Epoch 964/1400\n", + "28/28 [==============================] - 0s 902us/step - loss: 0.3810 - mse: 0.3947\n", + "Epoch 965/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 0.3793 - mse: 0.3965\n", + "Epoch 966/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.3796 - mse: 0.3898\n", + "Epoch 967/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3762 - mse: 0.3944\n", + "Epoch 968/1400\n", + "28/28 [==============================] - 0s 919us/step - loss: 0.3944 - mse: 0.4072\n", + "Epoch 969/1400\n", + "28/28 [==============================] - 0s 867us/step - loss: 0.3671 - mse: 0.3871\n", + "Epoch 970/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3863 - mse: 0.4024\n", + "Epoch 971/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 0.3832 - mse: 0.3993\n", + "Epoch 972/1400\n", + "28/28 [==============================] - 0s 881us/step - loss: 0.3858 - mse: 0.3958\n", + "Epoch 973/1400\n", + "28/28 [==============================] - 0s 891us/step - loss: 0.3693 - mse: 0.3899\n", + "Epoch 974/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3685 - mse: 0.3801\n", + "Epoch 975/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3697 - mse: 0.3913\n", + "Epoch 976/1400\n", + "28/28 [==============================] - 0s 892us/step - loss: 0.3758 - mse: 0.3895\n", + "Epoch 977/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.3723 - mse: 0.3918\n", + "Epoch 978/1400\n", + "28/28 [==============================] - 0s 975us/step - loss: 0.3729 - mse: 0.3908\n", + "Epoch 979/1400\n", + "28/28 [==============================] - 0s 873us/step - loss: 0.3866 - mse: 0.4010\n", + "Epoch 980/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 0.3711 - mse: 0.3881\n", + "Epoch 981/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3955 - mse: 0.4105\n", + "Epoch 982/1400\n", + "28/28 [==============================] - 0s 992us/step - loss: 0.3894 - mse: 0.4140\n", + "Epoch 983/1400\n", + "28/28 [==============================] - 0s 881us/step - loss: 0.3870 - mse: 0.3966\n", + "Epoch 984/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 0.3724 - mse: 0.3890\n", + "Epoch 985/1400\n", + "28/28 [==============================] - 0s 903us/step - loss: 0.3703 - mse: 0.3854\n", + "Epoch 986/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3769 - mse: 0.3868\n", + "Epoch 987/1400\n", + "28/28 [==============================] - 0s 948us/step - loss: 0.3662 - mse: 0.3875\n", + "Epoch 988/1400\n", + "28/28 [==============================] - 0s 942us/step - loss: 0.3755 - mse: 0.3909\n", + "Epoch 989/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.4008 - mse: 0.4099\n", + "Epoch 990/1400\n", + "28/28 [==============================] - 0s 918us/step - loss: 0.3601 - mse: 0.3784\n", + "Epoch 991/1400\n", + "28/28 [==============================] - 0s 866us/step - loss: 0.3652 - mse: 0.3843\n", + "Epoch 992/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 0.3741 - mse: 0.3923\n", + "Epoch 993/1400\n", + "28/28 [==============================] - 0s 935us/step - loss: 0.3682 - mse: 0.3854\n", + "Epoch 994/1400\n", + "28/28 [==============================] - 0s 891us/step - loss: 0.3773 - mse: 0.4016\n", + "Epoch 995/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.3843 - mse: 0.4035\n", + "Epoch 996/1400\n", + "28/28 [==============================] - 0s 976us/step - loss: 0.3700 - mse: 0.3857\n", + "Epoch 997/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 878us/step - loss: 0.3748 - mse: 0.3837\n", + "Epoch 998/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 0.3815 - mse: 0.3906\n", + "Epoch 999/1400\n", + "28/28 [==============================] - 0s 966us/step - loss: 0.3739 - mse: 0.3965\n", + "Epoch 1000/1400\n", + "28/28 [==============================] - 0s 913us/step - loss: 0.3688 - mse: 0.3881\n", + "Epoch 1001/1400\n", + "28/28 [==============================] - 0s 872us/step - loss: 0.3753 - mse: 0.3838\n", + "Epoch 1002/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 0.3637 - mse: 0.3772\n", + "Epoch 1003/1400\n", + "28/28 [==============================] - 0s 872us/step - loss: 0.3783 - mse: 0.4000\n", + "Epoch 1004/1400\n", + "28/28 [==============================] - 0s 864us/step - loss: 0.3744 - mse: 0.3893\n", + "Epoch 1005/1400\n", + "28/28 [==============================] - 0s 899us/step - loss: 0.3710 - mse: 0.3939\n", + "Epoch 1006/1400\n", + "28/28 [==============================] - 0s 887us/step - loss: 0.3707 - mse: 0.3814\n", + "Epoch 1007/1400\n", + "28/28 [==============================] - 0s 972us/step - loss: 0.3624 - mse: 0.3785\n", + "Epoch 1008/1400\n", + "28/28 [==============================] - 0s 955us/step - loss: 0.3646 - mse: 0.3867\n", + "Epoch 1009/1400\n", + "28/28 [==============================] - 0s 963us/step - loss: 0.3703 - mse: 0.3875\n", + "Epoch 1010/1400\n", + "28/28 [==============================] - 0s 985us/step - loss: 0.3947 - mse: 0.3975\n", + "Epoch 1011/1400\n", + "28/28 [==============================] - 0s 941us/step - loss: 0.3889 - mse: 0.4013\n", + "Epoch 1012/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3671 - mse: 0.3848\n", + "Epoch 1013/1400\n", + "28/28 [==============================] - 0s 990us/step - loss: 0.3624 - mse: 0.3783\n", + "Epoch 1014/1400\n", + "28/28 [==============================] - 0s 892us/step - loss: 0.3597 - mse: 0.3751\n", + "Epoch 1015/1400\n", + "28/28 [==============================] - 0s 899us/step - loss: 0.3574 - mse: 0.3783\n", + "Epoch 1016/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3601 - mse: 0.3778\n", + "Epoch 1017/1400\n", + "28/28 [==============================] - 0s 961us/step - loss: 0.3725 - mse: 0.3854\n", + "Epoch 1018/1400\n", + "28/28 [==============================] - 0s 935us/step - loss: 0.3720 - mse: 0.3791\n", + "Epoch 1019/1400\n", + "28/28 [==============================] - 0s 890us/step - loss: 0.3981 - mse: 0.4108\n", + "Epoch 1020/1400\n", + "28/28 [==============================] - 0s 992us/step - loss: 0.3901 - mse: 0.3944\n", + "Epoch 1021/1400\n", + "28/28 [==============================] - 0s 962us/step - loss: 0.3688 - mse: 0.3864\n", + "Epoch 1022/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 0.3853 - mse: 0.3866\n", + "Epoch 1023/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 0.3914 - mse: 0.3985\n", + "Epoch 1024/1400\n", + "28/28 [==============================] - 0s 963us/step - loss: 0.3734 - mse: 0.3752\n", + "Epoch 1025/1400\n", + "28/28 [==============================] - 0s 955us/step - loss: 0.3649 - mse: 0.3761\n", + "Epoch 1026/1400\n", + "28/28 [==============================] - 0s 935us/step - loss: 0.3817 - mse: 0.3852\n", + "Epoch 1027/1400\n", + "28/28 [==============================] - 0s 991us/step - loss: 0.3611 - mse: 0.3740\n", + "Epoch 1028/1400\n", + "28/28 [==============================] - 0s 877us/step - loss: 0.3753 - mse: 0.3827\n", + "Epoch 1029/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 0.3769 - mse: 0.3881\n", + "Epoch 1030/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.3662 - mse: 0.3788\n", + "Epoch 1031/1400\n", + "28/28 [==============================] - 0s 907us/step - loss: 0.3777 - mse: 0.3856\n", + "Epoch 1032/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.3839 - mse: 0.3889\n", + "Epoch 1033/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3688 - mse: 0.3793\n", + "Epoch 1034/1400\n", + "28/28 [==============================] - 0s 904us/step - loss: 0.3597 - mse: 0.3719\n", + "Epoch 1035/1400\n", + "28/28 [==============================] - 0s 959us/step - loss: 0.3772 - mse: 0.3849\n", + "Epoch 1036/1400\n", + "28/28 [==============================] - 0s 905us/step - loss: 0.3735 - mse: 0.3748\n", + "Epoch 1037/1400\n", + "28/28 [==============================] - 0s 881us/step - loss: 0.3724 - mse: 0.3786\n", + "Epoch 1038/1400\n", + "28/28 [==============================] - 0s 933us/step - loss: 0.3766 - mse: 0.3835\n", + "Epoch 1039/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.3987 - mse: 0.3974\n", + "Epoch 1040/1400\n", + "28/28 [==============================] - 0s 905us/step - loss: 0.3824 - mse: 0.3948\n", + "Epoch 1041/1400\n", + "28/28 [==============================] - 0s 897us/step - loss: 0.3655 - mse: 0.3744\n", + "Epoch 1042/1400\n", + "28/28 [==============================] - 0s 966us/step - loss: 0.3540 - mse: 0.3689\n", + "Epoch 1043/1400\n", + "28/28 [==============================] - 0s 891us/step - loss: 0.3714 - mse: 0.3844\n", + "Epoch 1044/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.3617 - mse: 0.3726\n", + "Epoch 1045/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.3625 - mse: 0.3771\n", + "Epoch 1046/1400\n", + "28/28 [==============================] - 0s 897us/step - loss: 0.3654 - mse: 0.3775\n", + "Epoch 1047/1400\n", + "28/28 [==============================] - 0s 915us/step - loss: 0.3679 - mse: 0.3812\n", + "Epoch 1048/1400\n", + "28/28 [==============================] - 0s 907us/step - loss: 0.3689 - mse: 0.3724\n", + "Epoch 1049/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.3857 - mse: 0.3852\n", + "Epoch 1050/1400\n", + "28/28 [==============================] - 0s 879us/step - loss: 0.3767 - mse: 0.3932\n", + "Epoch 1051/1400\n", + "28/28 [==============================] - 0s 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mse: 0.3646\n", + "Epoch 1078/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 0.3660 - mse: 0.3685\n", + "Epoch 1079/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 906us/step - loss: 0.3667 - mse: 0.3748\n", + "Epoch 1080/1400\n", + "28/28 [==============================] - 0s 993us/step - loss: 0.3640 - mse: 0.3670\n", + "Epoch 1081/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 0.3574 - mse: 0.3612\n", + "Epoch 1082/1400\n", + "28/28 [==============================] - 0s 994us/step - loss: 0.3630 - mse: 0.3653\n", + "Epoch 1083/1400\n", + "28/28 [==============================] - 0s 998us/step - loss: 0.3617 - mse: 0.3738\n", + "Epoch 1084/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3630 - mse: 0.3686\n", + "Epoch 1085/1400\n", + "28/28 [==============================] - 0s 888us/step - loss: 0.3727 - mse: 0.3707\n", + "Epoch 1086/1400\n", + "28/28 [==============================] - 0s 926us/step - loss: 0.3571 - mse: 0.3666\n", + "Epoch 1087/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 0.3630 - mse: 0.3646\n", + "Epoch 1088/1400\n", + "28/28 [==============================] - 0s 934us/step - loss: 0.3713 - mse: 0.3619\n", + "Epoch 1089/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.3702 - mse: 0.3748\n", + "Epoch 1090/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.3617 - mse: 0.3676\n", + "Epoch 1091/1400\n", + "28/28 [==============================] - 0s 899us/step - loss: 0.3639 - mse: 0.3668\n", + "Epoch 1092/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.3656 - mse: 0.3665\n", + "Epoch 1093/1400\n", + "28/28 [==============================] - 0s 997us/step - loss: 0.3584 - mse: 0.3634\n", + "Epoch 1094/1400\n", + "28/28 [==============================] - 0s 904us/step - loss: 0.3500 - mse: 0.3577\n", + "Epoch 1095/1400\n", + "28/28 [==============================] - 0s 930us/step - loss: 0.3577 - mse: 0.3654\n", + "Epoch 1096/1400\n", + "28/28 [==============================] - 0s 964us/step - loss: 0.3823 - mse: 0.3819\n", + "Epoch 1097/1400\n", + "28/28 [==============================] - 0s 904us/step - loss: 0.3790 - mse: 0.3855\n", + "Epoch 1098/1400\n", + "28/28 [==============================] - 0s 865us/step - loss: 0.3567 - mse: 0.3596\n", + "Epoch 1099/1400\n", + "28/28 [==============================] - 0s 880us/step - loss: 0.3648 - mse: 0.3677\n", + "Epoch 1100/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3565 - mse: 0.3598\n", + "Epoch 1101/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.3625 - mse: 0.3690\n", + "Epoch 1102/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3730 - mse: 0.3770\n", + "Epoch 1103/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 0.3520 - mse: 0.3634\n", + "Epoch 1104/1400\n", + "28/28 [==============================] - 0s 935us/step - loss: 0.3624 - mse: 0.3648\n", + "Epoch 1105/1400\n", + "28/28 [==============================] - 0s 869us/step - loss: 0.3584 - mse: 0.3689\n", + "Epoch 1106/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.3647 - mse: 0.3750\n", + "Epoch 1107/1400\n", + "28/28 [==============================] - 0s 849us/step - loss: 0.3612 - mse: 0.3650\n", + "Epoch 1108/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3706 - mse: 0.3762\n", + "Epoch 1109/1400\n", + "28/28 [==============================] - 0s 961us/step - loss: 0.3821 - mse: 0.3923\n", + "Epoch 1110/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.3569 - mse: 0.3606\n", + "Epoch 1111/1400\n", + "28/28 [==============================] - 0s 867us/step - loss: 0.3574 - mse: 0.3629\n", + "Epoch 1112/1400\n", + "28/28 [==============================] - 0s 881us/step - loss: 0.3571 - mse: 0.3621\n", + "Epoch 1113/1400\n", + "28/28 [==============================] - 0s 975us/step - loss: 0.3485 - mse: 0.3594\n", + "Epoch 1114/1400\n", + "28/28 [==============================] - 0s 893us/step - loss: 0.3943 - mse: 0.3985\n", + "Epoch 1115/1400\n", + "28/28 [==============================] - 0s 923us/step - loss: 0.3662 - mse: 0.3705\n", + "Epoch 1116/1400\n", + "28/28 [==============================] - 0s 880us/step - loss: 0.3626 - mse: 0.3656\n", + "Epoch 1117/1400\n", + "28/28 [==============================] - 0s 949us/step - loss: 0.3556 - mse: 0.3578\n", + "Epoch 1118/1400\n", + "28/28 [==============================] - 0s 916us/step - loss: 0.3579 - mse: 0.3615\n", + "Epoch 1119/1400\n", + "28/28 [==============================] - 0s 926us/step - loss: 0.3513 - mse: 0.3531\n", + "Epoch 1120/1400\n", + "28/28 [==============================] - 0s 877us/step - loss: 0.3551 - mse: 0.3642\n", + "Epoch 1121/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3495 - mse: 0.3615\n", + "Epoch 1122/1400\n", + "28/28 [==============================] - 0s 944us/step - loss: 0.3579 - mse: 0.3635\n", + "Epoch 1123/1400\n", + "28/28 [==============================] - 0s 864us/step - loss: 0.3569 - mse: 0.3645\n", + "Epoch 1124/1400\n", + "28/28 [==============================] - 0s 948us/step - loss: 0.3650 - mse: 0.3735\n", + "Epoch 1125/1400\n", + "28/28 [==============================] - 0s 968us/step - loss: 0.3494 - mse: 0.3549\n", + "Epoch 1126/1400\n", + "28/28 [==============================] - 0s 940us/step - loss: 0.3578 - mse: 0.3644\n", + "Epoch 1127/1400\n", + "28/28 [==============================] - 0s 856us/step - loss: 0.3592 - mse: 0.3628\n", + "Epoch 1128/1400\n", + "28/28 [==============================] - 0s 939us/step - loss: 0.3503 - mse: 0.3612\n", + "Epoch 1129/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 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[==============================] - 0s 917us/step - loss: 0.3758 - mse: 0.3833\n", + "Epoch 1148/1400\n", + "28/28 [==============================] - 0s 956us/step - loss: 0.3508 - mse: 0.3520\n", + "Epoch 1149/1400\n", + "28/28 [==============================] - 0s 880us/step - loss: 0.3647 - mse: 0.3667\n", + "Epoch 1150/1400\n", + "28/28 [==============================] - 0s 928us/step - loss: 0.3607 - mse: 0.3613\n", + "Epoch 1151/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.3555 - mse: 0.3623\n", + "Epoch 1152/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.3802 - mse: 0.3815\n", + "Epoch 1153/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.3806 - mse: 0.3747\n", + "Epoch 1154/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.3586 - mse: 0.3619\n", + "Epoch 1155/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3432 - mse: 0.3481\n", + "Epoch 1156/1400\n", + "28/28 [==============================] - 0s 873us/step - loss: 0.3537 - mse: 0.3523\n", + "Epoch 1157/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3589 - mse: 0.3588\n", + "Epoch 1158/1400\n", + "28/28 [==============================] - 0s 886us/step - loss: 0.3453 - mse: 0.3544\n", + "Epoch 1159/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 0.3487 - mse: 0.3548\n", + "Epoch 1160/1400\n", + "28/28 [==============================] - 0s 992us/step - loss: 0.3665 - mse: 0.3655\n", + "Epoch 1161/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 908us/step - loss: 0.3865 - mse: 0.3773\n", + "Epoch 1162/1400\n", + "28/28 [==============================] - 0s 878us/step - loss: 0.3749 - mse: 0.3706\n", + "Epoch 1163/1400\n", + "28/28 [==============================] - 0s 911us/step - loss: 0.3842 - mse: 0.3752\n", + "Epoch 1164/1400\n", + 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+ "Epoch 1173/1400\n", + "28/28 [==============================] - 0s 990us/step - loss: 0.3609 - mse: 0.3551\n", + "Epoch 1174/1400\n", + "28/28 [==============================] - 0s 935us/step - loss: 0.3580 - mse: 0.3495\n", + "Epoch 1175/1400\n", + "28/28 [==============================] - 0s 861us/step - loss: 0.3465 - mse: 0.3455\n", + "Epoch 1176/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.3531 - mse: 0.3630\n", + "Epoch 1177/1400\n", + "28/28 [==============================] - 0s 857us/step - loss: 0.3490 - mse: 0.3543\n", + "Epoch 1178/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.3709 - mse: 0.3705\n", + "Epoch 1179/1400\n", + "28/28 [==============================] - 0s 992us/step - loss: 0.3487 - mse: 0.3503\n", + "Epoch 1180/1400\n", + "28/28 [==============================] - 0s 952us/step - loss: 0.3436 - mse: 0.3508\n", + "Epoch 1181/1400\n", + "28/28 [==============================] - 0s 855us/step - loss: 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[==============================] - 0s 883us/step - loss: 0.3424 - mse: 0.3479\n", + "Epoch 1191/1400\n", + "28/28 [==============================] - 0s 912us/step - loss: 0.3655 - mse: 0.3585\n", + "Epoch 1192/1400\n", + "28/28 [==============================] - 0s 868us/step - loss: 0.3793 - mse: 0.3659\n", + "Epoch 1193/1400\n", + "28/28 [==============================] - 0s 944us/step - loss: 0.3622 - mse: 0.3598\n", + "Epoch 1194/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3492 - mse: 0.3501\n", + "Epoch 1195/1400\n", + "28/28 [==============================] - 0s 872us/step - loss: 0.3370 - mse: 0.3418\n", + "Epoch 1196/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3837 - mse: 0.3719\n", + "Epoch 1197/1400\n", + "28/28 [==============================] - 0s 931us/step - loss: 0.3683 - mse: 0.3568\n", + "Epoch 1198/1400\n", + "28/28 [==============================] - 0s 914us/step - loss: 0.3496 - mse: 0.3461\n", + "Epoch 1199/1400\n", + "28/28 [==============================] - 0s 878us/step - loss: 0.3447 - mse: 0.3454\n", + "Epoch 1200/1400\n", + "28/28 [==============================] - 0s 975us/step - loss: 0.3876 - mse: 0.3674\n", + "Epoch 1201/1400\n", + "28/28 [==============================] - 0s 926us/step - loss: 0.4028 - mse: 0.3979\n", + "Epoch 1202/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.3512 - mse: 0.3502\n", + "Epoch 1203/1400\n", + "28/28 [==============================] - 0s 959us/step - loss: 0.3570 - mse: 0.3546\n", + "Epoch 1204/1400\n", + "28/28 [==============================] - 0s 978us/step - loss: 0.3317 - mse: 0.3376\n", + "Epoch 1205/1400\n", + "28/28 [==============================] - 0s 872us/step - loss: 0.3472 - mse: 0.3436\n", + "Epoch 1206/1400\n", + "28/28 [==============================] - 0s 874us/step - loss: 0.3419 - mse: 0.3424\n", + "Epoch 1207/1400\n", + "28/28 [==============================] - 0s 911us/step - loss: 0.3452 - mse: 0.3500\n", + "Epoch 1208/1400\n", + "28/28 [==============================] - 0s 900us/step - loss: 0.3501 - mse: 0.3463\n", + "Epoch 1209/1400\n", + "28/28 [==============================] - 0s 901us/step - loss: 0.3347 - mse: 0.3335\n", + "Epoch 1210/1400\n", + "28/28 [==============================] - 0s 911us/step - loss: 0.3512 - mse: 0.3505\n", + "Epoch 1211/1400\n", + "28/28 [==============================] - 0s 937us/step - loss: 0.3572 - mse: 0.3589\n", + "Epoch 1212/1400\n", + "28/28 [==============================] - 0s 879us/step - loss: 0.3687 - mse: 0.3643\n", + "Epoch 1213/1400\n", + "28/28 [==============================] - 0s 900us/step - loss: 0.3643 - mse: 0.3547\n", + "Epoch 1214/1400\n", + "28/28 [==============================] - 0s 854us/step - loss: 0.3580 - mse: 0.3383\n", + "Epoch 1215/1400\n", + "28/28 [==============================] - 0s 937us/step - loss: 0.3631 - mse: 0.3477\n", + "Epoch 1216/1400\n", + "28/28 [==============================] - 0s 937us/step - loss: 0.3444 - mse: 0.3430\n", + "Epoch 1217/1400\n", + "28/28 [==============================] - 0s 880us/step - loss: 0.3490 - mse: 0.3449\n", + "Epoch 1218/1400\n", + "28/28 [==============================] - 0s 917us/step - loss: 0.3363 - mse: 0.3373\n", + "Epoch 1219/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.3327 - mse: 0.3411\n", + "Epoch 1220/1400\n", + "28/28 [==============================] - 0s 978us/step - loss: 0.3438 - mse: 0.3439\n", + "Epoch 1221/1400\n", + "28/28 [==============================] - 0s 888us/step - loss: 0.3484 - mse: 0.3482\n", + "Epoch 1222/1400\n", + "28/28 [==============================] - 0s 894us/step - loss: 0.3577 - mse: 0.3520\n", + "Epoch 1223/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3744 - mse: 0.3657\n", + "Epoch 1224/1400\n", + "28/28 [==============================] - 0s 938us/step - loss: 0.3593 - mse: 0.3419\n", + "Epoch 1225/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.3727 - mse: 0.3636\n", + "Epoch 1226/1400\n", + "28/28 [==============================] - 0s 919us/step - loss: 0.3527 - mse: 0.3479\n", + "Epoch 1227/1400\n", + "28/28 [==============================] - 0s 964us/step - loss: 0.3517 - mse: 0.3453\n", + "Epoch 1228/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3558 - mse: 0.3608\n", + "Epoch 1229/1400\n", + "28/28 [==============================] - 0s 935us/step - loss: 0.3505 - mse: 0.3458\n", + "Epoch 1230/1400\n", + "28/28 [==============================] - 0s 912us/step - loss: 0.3530 - mse: 0.3488\n", + "Epoch 1231/1400\n", + "28/28 [==============================] - 0s 942us/step - loss: 0.3566 - mse: 0.3541\n", + "Epoch 1232/1400\n", + "28/28 [==============================] - 0s 894us/step - loss: 0.3652 - mse: 0.3594\n", + "Epoch 1233/1400\n", + "28/28 [==============================] - 0s 880us/step - loss: 0.3587 - mse: 0.3507\n", + "Epoch 1234/1400\n", + "28/28 [==============================] - 0s 898us/step - loss: 0.3435 - mse: 0.3408\n", + "Epoch 1235/1400\n", + "28/28 [==============================] - 0s 991us/step - loss: 0.3582 - mse: 0.3574\n", + "Epoch 1236/1400\n", + "28/28 [==============================] - 0s 895us/step - loss: 0.3500 - mse: 0.3452\n", + "Epoch 1237/1400\n", + "28/28 [==============================] - 0s 879us/step - loss: 0.3666 - mse: 0.3544\n", + "Epoch 1238/1400\n", + "28/28 [==============================] - 0s 969us/step - loss: 0.3682 - mse: 0.3533\n", + "Epoch 1239/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.3726 - mse: 0.3602\n", + "Epoch 1240/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 0.3504 - mse: 0.3408\n", + "Epoch 1241/1400\n", + "28/28 [==============================] - 0s 958us/step - loss: 0.3609 - mse: 0.3506\n", + "Epoch 1242/1400\n", + "28/28 [==============================] - 0s 963us/step - loss: 0.3674 - mse: 0.3580\n", + "Epoch 1243/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 901us/step - loss: 0.3722 - mse: 0.3668\n", + "Epoch 1244/1400\n", + "28/28 [==============================] - 0s 854us/step - loss: 0.3627 - mse: 0.3506\n", + "Epoch 1245/1400\n", + "28/28 [==============================] - 0s 912us/step - loss: 0.3834 - mse: 0.3749\n", + "Epoch 1246/1400\n", + "28/28 [==============================] - 0s 890us/step - loss: 0.3365 - mse: 0.3362\n", + "Epoch 1247/1400\n", + "28/28 [==============================] - 0s 968us/step - loss: 0.3882 - mse: 0.3729\n", + "Epoch 1248/1400\n", + "28/28 [==============================] - 0s 922us/step - loss: 0.3597 - mse: 0.3409\n", + "Epoch 1249/1400\n", + "28/28 [==============================] - 0s 902us/step - loss: 0.3393 - mse: 0.3316\n", + "Epoch 1250/1400\n", + "28/28 [==============================] - 0s 878us/step - loss: 0.3465 - mse: 0.3345\n", + "Epoch 1251/1400\n", + "28/28 [==============================] - 0s 992us/step - loss: 0.3704 - mse: 0.3539\n", + "Epoch 1252/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3518 - mse: 0.3468\n", + "Epoch 1253/1400\n", + "28/28 [==============================] - 0s 871us/step - loss: 0.3311 - mse: 0.3298\n", + "Epoch 1254/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3563 - mse: 0.3527\n", + "Epoch 1255/1400\n", + "28/28 [==============================] - 0s 925us/step - loss: 0.3421 - mse: 0.3408\n", + "Epoch 1256/1400\n", + "28/28 [==============================] - 0s 858us/step - loss: 0.3716 - mse: 0.3604\n", + "Epoch 1257/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.3344 - mse: 0.3348\n", + "Epoch 1258/1400\n", + "28/28 [==============================] - 0s 871us/step - loss: 0.3466 - mse: 0.3408\n", + "Epoch 1259/1400\n", + "28/28 [==============================] - 0s 864us/step - loss: 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0s 1ms/step - loss: 0.3576 - mse: 0.3535\n", + "Epoch 1269/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3499 - mse: 0.3405\n", + "Epoch 1270/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.3624 - mse: 0.3508\n", + "Epoch 1271/1400\n", + "28/28 [==============================] - 0s 871us/step - loss: 0.3449 - mse: 0.3381\n", + "Epoch 1272/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.3646 - mse: 0.3516\n", + "Epoch 1273/1400\n", + "28/28 [==============================] - 0s 974us/step - loss: 0.3503 - mse: 0.3385\n", + "Epoch 1274/1400\n", + "28/28 [==============================] - 0s 878us/step - loss: 0.3353 - mse: 0.3305\n", + "Epoch 1275/1400\n", + "28/28 [==============================] - 0s 940us/step - loss: 0.3630 - mse: 0.3519\n", + "Epoch 1276/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.3564 - mse: 0.3354\n", + "Epoch 1277/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3812 - mse: 0.3622\n", + "Epoch 1278/1400\n", + "28/28 [==============================] - 0s 913us/step - loss: 0.3730 - mse: 0.3614\n", + "Epoch 1279/1400\n", + "28/28 [==============================] - 0s 895us/step - loss: 0.4151 - mse: 0.3931\n", + "Epoch 1280/1400\n", + "28/28 [==============================] - 0s 890us/step - loss: 0.3610 - mse: 0.3477\n", + "Epoch 1281/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3401 - mse: 0.3300\n", + "Epoch 1282/1400\n", + "28/28 [==============================] - 0s 885us/step - loss: 0.3477 - mse: 0.3385\n", + "Epoch 1283/1400\n", + "28/28 [==============================] - 0s 900us/step - loss: 0.3429 - mse: 0.3380\n", + "Epoch 1284/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3532 - mse: 0.3454\n", + "Epoch 1285/1400\n", + "28/28 [==============================] - 0s 966us/step - loss: 0.3475 - mse: 0.3393\n", + "Epoch 1286/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 0.3313 - mse: 0.3286\n", + "Epoch 1287/1400\n", + "28/28 [==============================] - 0s 2ms/step - loss: 0.3465 - mse: 0.3382\n", + "Epoch 1288/1400\n", + "28/28 [==============================] - 0s 998us/step - loss: 0.3476 - mse: 0.3471\n", + "Epoch 1289/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.3530 - mse: 0.3455\n", + "Epoch 1290/1400\n", + "28/28 [==============================] - 0s 897us/step - loss: 0.3349 - mse: 0.3330\n", + "Epoch 1291/1400\n", + "28/28 [==============================] - 0s 995us/step - loss: 0.3544 - mse: 0.3375\n", + "Epoch 1292/1400\n", + "28/28 [==============================] - 0s 883us/step - loss: 0.3322 - mse: 0.3302\n", + "Epoch 1293/1400\n", + "28/28 [==============================] - 0s 902us/step - loss: 0.3438 - mse: 0.3326\n", + "Epoch 1294/1400\n", + "28/28 [==============================] - 0s 920us/step - loss: 0.3571 - mse: 0.3429\n", + "Epoch 1295/1400\n", + "28/28 [==============================] - 0s 973us/step - loss: 0.3558 - mse: 0.3424\n", + "Epoch 1296/1400\n", + "28/28 [==============================] - 0s 899us/step - loss: 0.3377 - mse: 0.3333\n", + "Epoch 1297/1400\n", + "28/28 [==============================] - 0s 970us/step - loss: 0.3432 - mse: 0.3278\n", + "Epoch 1298/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3237 - mse: 0.3228\n", + "Epoch 1299/1400\n", + "28/28 [==============================] - 0s 912us/step - loss: 0.3395 - mse: 0.3310\n", + "Epoch 1300/1400\n", + "28/28 [==============================] - 0s 883us/step - loss: 0.3365 - mse: 0.3374\n", + "Epoch 1301/1400\n", + "28/28 [==============================] - 0s 968us/step - loss: 0.3564 - mse: 0.3435\n", + "Epoch 1302/1400\n", + "28/28 [==============================] - 0s 899us/step - loss: 0.3372 - mse: 0.3336\n", + "Epoch 1303/1400\n", + "28/28 [==============================] - 0s 886us/step - loss: 0.3467 - mse: 0.3374\n", + "Epoch 1304/1400\n", + "28/28 [==============================] - 0s 939us/step - loss: 0.3478 - mse: 0.3319\n", + "Epoch 1305/1400\n", + "28/28 [==============================] - 0s 994us/step - loss: 0.3493 - mse: 0.3358\n", + "Epoch 1306/1400\n", + "28/28 [==============================] - 0s 941us/step - loss: 0.3780 - mse: 0.3501\n", + "Epoch 1307/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.3435 - mse: 0.3252\n", + "Epoch 1308/1400\n", + "28/28 [==============================] - 0s 915us/step - loss: 0.3381 - mse: 0.3302\n", + "Epoch 1309/1400\n", + "28/28 [==============================] - 0s 899us/step - loss: 0.3436 - mse: 0.3358\n", + "Epoch 1310/1400\n", + "28/28 [==============================] - 0s 889us/step - loss: 0.3561 - mse: 0.3523\n", + "Epoch 1311/1400\n", + "28/28 [==============================] - 0s 979us/step - loss: 0.3361 - mse: 0.3323\n", + "Epoch 1312/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 0.3595 - mse: 0.3519\n", + "Epoch 1313/1400\n", + "28/28 [==============================] - 0s 865us/step - loss: 0.3386 - mse: 0.3338\n", + "Epoch 1314/1400\n", + "28/28 [==============================] - 0s 927us/step - loss: 0.3340 - mse: 0.3288\n", + "Epoch 1315/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 0.3296 - mse: 0.3267\n", + "Epoch 1316/1400\n", + "28/28 [==============================] - 0s 879us/step - loss: 0.3558 - mse: 0.3438\n", + "Epoch 1317/1400\n", + "28/28 [==============================] - 0s 919us/step - loss: 0.3400 - mse: 0.3341\n", + "Epoch 1318/1400\n", + "28/28 [==============================] - 0s 868us/step - loss: 0.3278 - mse: 0.3221\n", + "Epoch 1319/1400\n", + "28/28 [==============================] - 0s 906us/step - loss: 0.3390 - mse: 0.3332\n", + "Epoch 1320/1400\n", + "28/28 [==============================] - 0s 932us/step - loss: 0.3362 - mse: 0.3278\n", + "Epoch 1321/1400\n", + "28/28 [==============================] - 0s 978us/step - loss: 0.3427 - mse: 0.3284\n", + "Epoch 1322/1400\n", + "28/28 [==============================] - 0s 901us/step - loss: 0.3412 - mse: 0.3318\n", + "Epoch 1323/1400\n", + "28/28 [==============================] - 0s 950us/step - loss: 0.3252 - mse: 0.3152\n", + "Epoch 1324/1400\n", + "28/28 [==============================] - 0s 890us/step - loss: 0.3505 - mse: 0.3447\n", + "Epoch 1325/1400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "28/28 [==============================] - 0s 866us/step - loss: 0.3347 - mse: 0.3251\n", + "Epoch 1326/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3415 - mse: 0.3337\n", + "Epoch 1327/1400\n", + "28/28 [==============================] - 0s 903us/step - loss: 0.3312 - mse: 0.3283\n", + "Epoch 1328/1400\n", + "28/28 [==============================] - 0s 856us/step - loss: 0.3333 - mse: 0.3218\n", + "Epoch 1329/1400\n", + "28/28 [==============================] - 0s 933us/step - loss: 0.3557 - mse: 0.3418\n", + "Epoch 1330/1400\n", + "28/28 [==============================] - 0s 967us/step - loss: 0.3502 - mse: 0.3411\n", + "Epoch 1331/1400\n", + "28/28 [==============================] - 0s 887us/step - loss: 0.3480 - mse: 0.3431\n", + "Epoch 1332/1400\n", + "28/28 [==============================] - 0s 904us/step - loss: 0.3449 - mse: 0.3432\n", + "Epoch 1333/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3512 - mse: 0.3472\n", + "Epoch 1334/1400\n", + "28/28 [==============================] - 0s 957us/step - loss: 0.3365 - mse: 0.3284\n", + "Epoch 1335/1400\n", + "28/28 [==============================] - 0s 903us/step - loss: 0.3359 - mse: 0.3304\n", + "Epoch 1336/1400\n", + "28/28 [==============================] - 0s 910us/step - loss: 0.3255 - mse: 0.3258\n", + "Epoch 1337/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.3264 - mse: 0.3277\n", + "Epoch 1338/1400\n", + "28/28 [==============================] - 0s 943us/step - loss: 0.3347 - mse: 0.3273\n", + "Epoch 1339/1400\n", + "28/28 [==============================] - 0s 913us/step - loss: 0.3387 - mse: 0.3313\n", + "Epoch 1340/1400\n", + "28/28 [==============================] - 0s 871us/step - loss: 0.3301 - mse: 0.3267\n", + "Epoch 1341/1400\n", + "28/28 [==============================] - 0s 863us/step - loss: 0.3549 - mse: 0.3402\n", + "Epoch 1342/1400\n", + "28/28 [==============================] - 0s 893us/step - loss: 0.3308 - mse: 0.3255\n", + "Epoch 1343/1400\n", + "28/28 [==============================] - 0s 901us/step - loss: 0.3314 - mse: 0.3291\n", + "Epoch 1344/1400\n", + "28/28 [==============================] - 0s 924us/step - loss: 0.3371 - mse: 0.3310\n", + "Epoch 1345/1400\n", + "28/28 [==============================] - 0s 911us/step - loss: 0.3467 - mse: 0.3321\n", + "Epoch 1346/1400\n", + "28/28 [==============================] - 0s 906us/step - loss: 0.3266 - mse: 0.3224\n", + "Epoch 1347/1400\n", + "28/28 [==============================] - 0s 866us/step - loss: 0.3338 - mse: 0.3321\n", + "Epoch 1348/1400\n", + "28/28 [==============================] - 0s 866us/step - loss: 0.3281 - mse: 0.3252\n", + "Epoch 1349/1400\n", + "28/28 [==============================] - 0s 961us/step - loss: 0.3621 - mse: 0.3515\n", + "Epoch 1350/1400\n", + "28/28 [==============================] - 0s 895us/step - loss: 0.3551 - mse: 0.3396\n", + "Epoch 1351/1400\n", + "28/28 [==============================] - 0s 934us/step - loss: 0.3365 - mse: 0.3264\n", + "Epoch 1352/1400\n", + "28/28 [==============================] - 0s 874us/step - loss: 0.3407 - mse: 0.3258\n", + "Epoch 1353/1400\n", + "28/28 [==============================] - 0s 933us/step - loss: 0.3423 - mse: 0.3391\n", + "Epoch 1354/1400\n", + "28/28 [==============================] - 0s 938us/step - loss: 0.3257 - mse: 0.3251\n", + "Epoch 1355/1400\n", + "28/28 [==============================] - 0s 876us/step - loss: 0.3189 - mse: 0.3198\n", + "Epoch 1356/1400\n", + "28/28 [==============================] - 0s 866us/step - loss: 0.3374 - mse: 0.3247\n", + "Epoch 1357/1400\n", + "28/28 [==============================] - 0s 923us/step - loss: 0.3542 - mse: 0.3415\n", + "Epoch 1358/1400\n", + "28/28 [==============================] - 0s 994us/step - loss: 0.3422 - mse: 0.3318\n", + "Epoch 1359/1400\n", + "28/28 [==============================] - 0s 864us/step - loss: 0.3428 - mse: 0.3263\n", + "Epoch 1360/1400\n", + "28/28 [==============================] - 0s 939us/step - loss: 0.3444 - mse: 0.3300\n", + "Epoch 1361/1400\n", + "28/28 [==============================] - 0s 900us/step - loss: 0.3282 - mse: 0.3197\n", + "Epoch 1362/1400\n", + "28/28 [==============================] - 0s 967us/step - loss: 0.3271 - mse: 0.3218\n", + "Epoch 1363/1400\n", + "28/28 [==============================] - 0s 922us/step - loss: 0.3264 - mse: 0.3182\n", + "Epoch 1364/1400\n", + "28/28 [==============================] - 0s 890us/step - loss: 0.3324 - mse: 0.3259\n", + "Epoch 1365/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3343 - mse: 0.3291\n", + "Epoch 1366/1400\n", + "28/28 [==============================] - 0s 953us/step - loss: 0.3281 - mse: 0.3275\n", + "Epoch 1367/1400\n", + "28/28 [==============================] - 0s 921us/step - loss: 0.3458 - mse: 0.3348\n", + "Epoch 1368/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.3392 - mse: 0.3242\n", + "Epoch 1369/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3406 - mse: 0.3290\n", + "Epoch 1370/1400\n", + "28/28 [==============================] - 0s 929us/step - loss: 0.3660 - mse: 0.3450\n", + "Epoch 1371/1400\n", + "28/28 [==============================] - 0s 908us/step - loss: 0.3306 - mse: 0.3230\n", + "Epoch 1372/1400\n", + "28/28 [==============================] - 0s 953us/step - loss: 0.3563 - mse: 0.3329\n", + "Epoch 1373/1400\n", + "28/28 [==============================] - 0s 868us/step - loss: 0.3304 - mse: 0.3259\n", + "Epoch 1374/1400\n", + "28/28 [==============================] - 0s 912us/step - loss: 0.3265 - mse: 0.3191\n", + "Epoch 1375/1400\n", + "28/28 [==============================] - 0s 936us/step - loss: 0.3283 - mse: 0.3266\n", + "Epoch 1376/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3604 - mse: 0.3384\n", + "Epoch 1377/1400\n", + "28/28 [==============================] - 0s 944us/step - loss: 0.3668 - mse: 0.3460\n", + "Epoch 1378/1400\n", + "28/28 [==============================] - 0s 899us/step - loss: 0.3351 - mse: 0.3207\n", + "Epoch 1379/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.3422 - mse: 0.3224\n", + "Epoch 1380/1400\n", + "28/28 [==============================] - 0s 938us/step - loss: 0.3473 - mse: 0.3356\n", + "Epoch 1381/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3462 - mse: 0.3266\n", + "Epoch 1382/1400\n", + "28/28 [==============================] - 0s 875us/step - loss: 0.3252 - mse: 0.3208\n", + "Epoch 1383/1400\n", + "28/28 [==============================] - 0s 893us/step - loss: 0.3460 - mse: 0.3321\n", + "Epoch 1384/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 0.3585 - mse: 0.3450\n", + "Epoch 1385/1400\n", + "28/28 [==============================] - 0s 896us/step - loss: 0.3713 - mse: 0.3553\n", + "Epoch 1386/1400\n", + "28/28 [==============================] - 0s 872us/step - loss: 0.3336 - mse: 0.3183\n", + "Epoch 1387/1400\n", + "28/28 [==============================] - 0s 992us/step - loss: 0.3331 - mse: 0.3207\n", + "Epoch 1388/1400\n", + "28/28 [==============================] - 0s 973us/step - loss: 0.3449 - mse: 0.3315\n", + "Epoch 1389/1400\n", + "28/28 [==============================] - 0s 874us/step - loss: 0.3463 - mse: 0.3246\n", + "Epoch 1390/1400\n", + "28/28 [==============================] - 0s 1ms/step - loss: 0.3330 - mse: 0.3184\n", + "Epoch 1391/1400\n", + "28/28 [==============================] - 0s 986us/step - loss: 0.3280 - mse: 0.3218\n", + "Epoch 1392/1400\n", + "28/28 [==============================] - 0s 969us/step - loss: 0.3529 - mse: 0.3421\n", + "Epoch 1393/1400\n", + "28/28 [==============================] - 0s 870us/step - loss: 0.3371 - mse: 0.3188\n", + "Epoch 1394/1400\n", + "28/28 [==============================] - 0s 891us/step - loss: 0.3380 - mse: 0.3255\n", + "Epoch 1395/1400\n", + "28/28 [==============================] - 0s 916us/step - loss: 0.3404 - mse: 0.3204\n", + "Epoch 1396/1400\n", + "28/28 [==============================] - 0s 991us/step - loss: 0.3322 - mse: 0.3203\n", + "Epoch 1397/1400\n", + "28/28 [==============================] - 0s 884us/step - loss: 0.3304 - mse: 0.3268\n", + "Epoch 1398/1400\n", + "28/28 [==============================] - 0s 933us/step - loss: 0.3310 - mse: 0.3221\n", + "Epoch 1399/1400\n", + "28/28 [==============================] - 0s 861us/step - loss: 0.3268 - mse: 0.3206\n", + "Epoch 1400/1400\n", + "28/28 [==============================] - 0s 932us/step - loss: 0.3366 - mse: 0.3248\n" + ] + } + ], + "source": [ + "model = Sequential()\n", + "model.add(Dense(100, input_dim = X_train.shape[1], activation='relu'))\n", + "model.add(Dense(1))\n", + "model.compile(loss='mae', optimizer=keras.optimizers.adam_v2.Adam(learning_rate=0.001), metrics=['mse'])\n", + "history = model.fit(X_train, y_train, epochs=1400)" + ] + }, + { + "cell_type": "code", + "execution_count": 437, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.2020128423439302\n", + "0.5789823493744719\n" + ] + } + ], + "source": [ + "print(np.linalg.norm(model.predict(X_valid).T - y_valid)/np.sqrt(len(y_valid)))\n", + "print(np.linalg.norm(model.predict(X_train).T - y_train)/np.sqrt(len(y_train)))" + ] + }, + { + "cell_type": "code", + "execution_count": 438, + "metadata": {}, + "outputs": [], + "source": [ + "prediction = model.predict(X)\n", + "np.savetxt('my_Temperature_prediction.csv', prediction, delimiter=',') " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/freezing_fritz/data_test_Temperature.csv b/freezing_fritz/data_test_Temperature.csv @@ -0,0 +1,101 @@ +Window 1,Window 2,Window 3,Window 4,Heat Control 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of Mystery Machine.ipynb diff --git a/ass01/PhilippPetersens_prediction.csv b/mistery_machine/PhilippPetersens_prediction.csv diff --git a/ass01/data_test_db.csv b/mistery_machine/data_test_db.csv diff --git a/ass01/data_train_db.csv b/mistery_machine/data_train_db.csv diff --git a/ass01/prediction.csv b/mistery_machine/prediction.csv