TurnUpTheHeat_Evaluation.ipynb - mlearn - Mathematics of Machine Learning

TurnUpTheHeat_Evaluation.ipynb (369309B)
      1 {
      2  "cells": [
      3   {
      4    "cell_type": "code",
      5    "execution_count": 1,
      6    "metadata": {},
      7    "outputs": [],
      8    "source": [
      9     "import numpy as np\n",
     10     "import matplotlib as mpl\n",
     11     "import matplotlib.pyplot as plt\n",
     12     "from matplotlib.pyplot import ion\n",
     13     "from scipy.signal import convolve2d\n",
     14     "import pandas as pd\n",
     15     "import seaborn as sn\n",
     16     "from sklearn.model_selection import train_test_split"
     17    ]
     18   },
     19   {
     20    "cell_type": "markdown",
     21    "metadata": {},
     22    "source": [
     23     "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",
     24     "\n",
     25     "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",
     26     "\n",
     27     "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",
     28     "\n",
     29     "Can you help Freezing Fritz to find blissful sleep?\n",
     30     "\n",
     31     "\n",
     32     "Let us first look at the situation. In the lecture notes you will find the experiment that Fritz carried out described in 8 cases."
     33    ]
     34   },
     35   {
     36    "cell_type": "markdown",
     37    "metadata": {},
     38    "source": [
     39     "For the experiment, we first load the data"
     40    ]
     41   },
     42   {
     43    "cell_type": "code",
     44    "execution_count": 2,
     45    "metadata": {},
     46    "outputs": [
     47     {
     48      "data": {
     49       "text/html": [
     50        "<div>\n",
     51        "<style scoped>\n",
     52        "    .dataframe tbody tr th:only-of-type {\n",
     53        "        vertical-align: middle;\n",
     54        "    }\n",
     55        "\n",
     56        "    .dataframe tbody tr th {\n",
     57        "        vertical-align: top;\n",
     58        "    }\n",
     59        "\n",
     60        "    .dataframe thead th {\n",
     61        "        text-align: right;\n",
     62        "    }\n",
     63        "</style>\n",
     64        "<table border=\"1\" class=\"dataframe\">\n",
     65        "  <thead>\n",
     66        "    <tr style=\"text-align: right;\">\n",
     67        "      <th></th>\n",
     68        "      <th>Window 1</th>\n",
     69        "      <th>Window 2</th>\n",
     70        "      <th>Window 3</th>\n",
     71        "      <th>Window 4</th>\n",
     72        "      <th>Heat Control 1</th>\n",
     73        "      <th>Heat Control 2</th>\n",
     74        "      <th>Heat Control 3</th>\n",
     75        "      <th>Heat Control 4</th>\n",
     76        "      <th>Door 1</th>\n",
     77        "      <th>Door 2</th>\n",
     78        "      <th>Door 3</th>\n",
     79        "      <th>Temperature Outside</th>\n",
     80        "      <th>Temperature Bed</th>\n",
     81        "    </tr>\n",
     82        "  </thead>\n",
     83        "  <tbody>\n",
     84        "    <tr>\n",
     85        "      <th>0</th>\n",
     86        "      <td>0.0</td>\n",
     87        "      <td>1.0</td>\n",
     88        "      <td>1.0</td>\n",
     89        "      <td>1.0</td>\n",
     90        "      <td>4.0</td>\n",
     91        "      <td>3.0</td>\n",
     92        "      <td>5.0</td>\n",
     93        "      <td>0.0</td>\n",
     94        "      <td>1.0</td>\n",
     95        "      <td>0.0</td>\n",
     96        "      <td>1.0</td>\n",
     97        "      <td>21.421148</td>\n",
     98        "      <td>-20.0</td>\n",
     99        "    </tr>\n",
    100        "    <tr>\n",
    101        "      <th>1</th>\n",
    102        "      <td>0.0</td>\n",
    103        "      <td>0.0</td>\n",
    104        "      <td>0.0</td>\n",
    105        "      <td>0.0</td>\n",
    106        "      <td>0.0</td>\n",
    107        "      <td>1.0</td>\n",
    108        "      <td>5.0</td>\n",
    109        "      <td>3.0</td>\n",
    110        "      <td>1.0</td>\n",
    111        "      <td>1.0</td>\n",
    112        "      <td>0.0</td>\n",
    113        "      <td>13.853981</td>\n",
    114        "      <td>-20.0</td>\n",
    115        "    </tr>\n",
    116        "    <tr>\n",
    117        "      <th>2</th>\n",
    118        "      <td>1.0</td>\n",
    119        "      <td>0.0</td>\n",
    120        "      <td>1.0</td>\n",
    121        "      <td>1.0</td>\n",
    122        "      <td>3.0</td>\n",
    123        "      <td>1.0</td>\n",
    124        "      <td>3.0</td>\n",
    125        "      <td>5.0</td>\n",
    126        "      <td>1.0</td>\n",
    127        "      <td>0.0</td>\n",
    128        "      <td>0.0</td>\n",
    129        "      <td>-1.493988</td>\n",
    130        "      <td>-20.0</td>\n",
    131        "    </tr>\n",
    132        "    <tr>\n",
    133        "      <th>3</th>\n",
    134        "      <td>1.0</td>\n",
    135        "      <td>1.0</td>\n",
    136        "      <td>1.0</td>\n",
    137        "      <td>1.0</td>\n",
    138        "      <td>3.0</td>\n",
    139        "      <td>0.0</td>\n",
    140        "      <td>1.0</td>\n",
    141        "      <td>0.0</td>\n",
    142        "      <td>1.0</td>\n",
    143        "      <td>0.0</td>\n",
    144        "      <td>1.0</td>\n",
    145        "      <td>1.787096</td>\n",
    146        "      <td>-20.0</td>\n",
    147        "    </tr>\n",
    148        "    <tr>\n",
    149        "      <th>4</th>\n",
    150        "      <td>1.0</td>\n",
    151        "      <td>1.0</td>\n",
    152        "      <td>1.0</td>\n",
    153        "      <td>1.0</td>\n",
    154        "      <td>0.0</td>\n",
    155        "      <td>5.0</td>\n",
    156        "      <td>5.0</td>\n",
    157        "      <td>5.0</td>\n",
    158        "      <td>1.0</td>\n",
    159        "      <td>1.0</td>\n",
    160        "      <td>1.0</td>\n",
    161        "      <td>-3.007195</td>\n",
    162        "      <td>-20.0</td>\n",
    163        "    </tr>\n",
    164        "  </tbody>\n",
    165        "</table>\n",
    166        "</div>"
    167       ],
    168       "text/plain": [
    169        "   Window 1  Window 2  Window 3  Window 4  Heat Control 1  Heat Control 2  \\\n",
    170        "0       0.0       1.0       1.0       1.0             4.0             3.0   \n",
    171        "1       0.0       0.0       0.0       0.0             0.0             1.0   \n",
    172        "2       1.0       0.0       1.0       1.0             3.0             1.0   \n",
    173        "3       1.0       1.0       1.0       1.0             3.0             0.0   \n",
    174        "4       1.0       1.0       1.0       1.0             0.0             5.0   \n",
    175        "\n",
    176        "   Heat Control 3  Heat Control 4  Door 1  Door 2  Door 3  \\\n",
    177        "0             5.0             0.0     1.0     0.0     1.0   \n",
    178        "1             5.0             3.0     1.0     1.0     0.0   \n",
    179        "2             3.0             5.0     1.0     0.0     0.0   \n",
    180        "3             1.0             0.0     1.0     0.0     1.0   \n",
    181        "4             5.0             5.0     1.0     1.0     1.0   \n",
    182        "\n",
    183        "   Temperature Outside  Temperature Bed  \n",
    184        "0            21.421148            -20.0  \n",
    185        "1            13.853981            -20.0  \n",
    186        "2            -1.493988            -20.0  \n",
    187        "3             1.787096            -20.0  \n",
    188        "4            -3.007195            -20.0  "
    189       ]
    190      },
    191      "execution_count": 2,
    192      "metadata": {},
    193      "output_type": "execute_result"
    194     }
    195    ],
    196    "source": [
    197     "data_train_Temperature = pd.read_csv('data_train_Temperature.csv')\n",
    198     "data_test_Temperature = pd.read_csv('data_test_Temperature.csv')\n",
    199     "data_test_Temperature.head()"
    200    ]
    201   },
    202   {
    203    "cell_type": "code",
    204    "execution_count": 3,
    205    "metadata": {},
    206    "outputs": [
    207     {
    208      "data": {
    209       "text/html": [
    210        "<div>\n",
    211        "<style scoped>\n",
    212        "    .dataframe tbody tr th:only-of-type {\n",
    213        "        vertical-align: middle;\n",
    214        "    }\n",
    215        "\n",
    216        "    .dataframe tbody tr th {\n",
    217        "        vertical-align: top;\n",
    218        "    }\n",
    219        "\n",
    220        "    .dataframe thead th {\n",
    221        "        text-align: right;\n",
    222        "    }\n",
    223        "</style>\n",
    224        "<table border=\"1\" class=\"dataframe\">\n",
    225        "  <thead>\n",
    226        "    <tr style=\"text-align: right;\">\n",
    227        "      <th></th>\n",
    228        "      <th>Window 1</th>\n",
    229        "      <th>Window 2</th>\n",
    230        "      <th>Window 3</th>\n",
    231        "      <th>Window 4</th>\n",
    232        "      <th>Heat Control 1</th>\n",
    233        "      <th>Heat Control 2</th>\n",
    234        "      <th>Heat Control 3</th>\n",
    235        "      <th>Heat Control 4</th>\n",
    236        "      <th>Door 1</th>\n",
    237        "      <th>Door 2</th>\n",
    238        "      <th>Door 3</th>\n",
    239        "      <th>Temperature Outside</th>\n",
    240        "      <th>Temperature Bed</th>\n",
    241        "    </tr>\n",
    242        "  </thead>\n",
    243        "  <tbody>\n",
    244        "    <tr>\n",
    245        "      <th>0</th>\n",
    246        "      <td>1.0</td>\n",
    247        "      <td>1.0</td>\n",
    248        "      <td>0.0</td>\n",
    249        "      <td>0.0</td>\n",
    250        "      <td>1.0</td>\n",
    251        "      <td>5.0</td>\n",
    252        "      <td>0.0</td>\n",
    253        "      <td>0.0</td>\n",
    254        "      <td>1.0</td>\n",
    255        "      <td>1.0</td>\n",
    256        "      <td>1.0</td>\n",
    257        "      <td>8.314993</td>\n",
    258        "      <td>17.260793</td>\n",
    259        "    </tr>\n",
    260        "    <tr>\n",
    261        "      <th>1</th>\n",
    262        "      <td>0.0</td>\n",
    263        "      <td>0.0</td>\n",
    264        "      <td>0.0</td>\n",
    265        "      <td>1.0</td>\n",
    266        "      <td>3.0</td>\n",
    267        "      <td>4.0</td>\n",
    268        "      <td>2.0</td>\n",
    269        "      <td>0.0</td>\n",
    270        "      <td>1.0</td>\n",
    271        "      <td>1.0</td>\n",
    272        "      <td>0.0</td>\n",
    273        "      <td>7.422077</td>\n",
    274        "      <td>16.479440</td>\n",
    275        "    </tr>\n",
    276        "    <tr>\n",
    277        "      <th>2</th>\n",
    278        "      <td>1.0</td>\n",
    279        "      <td>1.0</td>\n",
    280        "      <td>0.0</td>\n",
    281        "      <td>1.0</td>\n",
    282        "      <td>5.0</td>\n",
    283        "      <td>5.0</td>\n",
    284        "      <td>1.0</td>\n",
    285        "      <td>1.0</td>\n",
    286        "      <td>0.0</td>\n",
    287        "      <td>1.0</td>\n",
    288        "      <td>0.0</td>\n",
    289        "      <td>3.131294</td>\n",
    290        "      <td>13.649173</td>\n",
    291        "    </tr>\n",
    292        "    <tr>\n",
    293        "      <th>3</th>\n",
    294        "      <td>0.0</td>\n",
    295        "      <td>1.0</td>\n",
    296        "      <td>0.0</td>\n",
    297        "      <td>0.0</td>\n",
    298        "      <td>3.0</td>\n",
    299        "      <td>1.0</td>\n",
    300        "      <td>4.0</td>\n",
    301        "      <td>4.0</td>\n",
    302        "      <td>0.0</td>\n",
    303        "      <td>1.0</td>\n",
    304        "      <td>0.0</td>\n",
    305        "      <td>19.621818</td>\n",
    306        "      <td>27.223802</td>\n",
    307        "    </tr>\n",
    308        "    <tr>\n",
    309        "      <th>4</th>\n",
    310        "      <td>1.0</td>\n",
    311        "      <td>1.0</td>\n",
    312        "      <td>1.0</td>\n",
    313        "      <td>0.0</td>\n",
    314        "      <td>2.0</td>\n",
    315        "      <td>2.0</td>\n",
    316        "      <td>2.0</td>\n",
    317        "      <td>0.0</td>\n",
    318        "      <td>1.0</td>\n",
    319        "      <td>1.0</td>\n",
    320        "      <td>0.0</td>\n",
    321        "      <td>19.382874</td>\n",
    322        "      <td>23.714690</td>\n",
    323        "    </tr>\n",
    324        "    <tr>\n",
    325        "      <th>...</th>\n",
    326        "      <td>...</td>\n",
    327        "      <td>...</td>\n",
    328        "      <td>...</td>\n",
    329        "      <td>...</td>\n",
    330        "      <td>...</td>\n",
    331        "      <td>...</td>\n",
    332        "      <td>...</td>\n",
    333        "      <td>...</td>\n",
    334        "      <td>...</td>\n",
    335        "      <td>...</td>\n",
    336        "      <td>...</td>\n",
    337        "      <td>...</td>\n",
    338        "      <td>...</td>\n",
    339        "    </tr>\n",
    340        "    <tr>\n",
    341        "      <th>1090</th>\n",
    342        "      <td>0.0</td>\n",
    343        "      <td>0.0</td>\n",
    344        "      <td>1.0</td>\n",
    345        "      <td>1.0</td>\n",
    346        "      <td>0.0</td>\n",
    347        "      <td>0.0</td>\n",
    348        "      <td>5.0</td>\n",
    349        "      <td>5.0</td>\n",
    350        "      <td>1.0</td>\n",
    351        "      <td>0.0</td>\n",
    352        "      <td>0.0</td>\n",
    353        "      <td>-2.980819</td>\n",
    354        "      <td>3.779726</td>\n",
    355        "    </tr>\n",
    356        "    <tr>\n",
    357        "      <th>1091</th>\n",
    358        "      <td>1.0</td>\n",
    359        "      <td>1.0</td>\n",
    360        "      <td>1.0</td>\n",
    361        "      <td>0.0</td>\n",
    362        "      <td>5.0</td>\n",
    363        "      <td>0.0</td>\n",
    364        "      <td>2.0</td>\n",
    365        "      <td>2.0</td>\n",
    366        "      <td>0.0</td>\n",
    367        "      <td>1.0</td>\n",
    368        "      <td>1.0</td>\n",
    369        "      <td>6.322275</td>\n",
    370        "      <td>17.002934</td>\n",
    371        "    </tr>\n",
    372        "    <tr>\n",
    373        "      <th>1092</th>\n",
    374        "      <td>1.0</td>\n",
    375        "      <td>1.0</td>\n",
    376        "      <td>1.0</td>\n",
    377        "      <td>0.0</td>\n",
    378        "      <td>4.0</td>\n",
    379        "      <td>2.0</td>\n",
    380        "      <td>3.0</td>\n",
    381        "      <td>5.0</td>\n",
    382        "      <td>1.0</td>\n",
    383        "      <td>0.0</td>\n",
    384        "      <td>1.0</td>\n",
    385        "      <td>-1.224444</td>\n",
    386        "      <td>13.168637</td>\n",
    387        "    </tr>\n",
    388        "    <tr>\n",
    389        "      <th>1093</th>\n",
    390        "      <td>0.0</td>\n",
    391        "      <td>0.0</td>\n",
    392        "      <td>1.0</td>\n",
    393        "      <td>1.0</td>\n",
    394        "      <td>4.0</td>\n",
    395        "      <td>2.0</td>\n",
    396        "      <td>5.0</td>\n",
    397        "      <td>5.0</td>\n",
    398        "      <td>0.0</td>\n",
    399        "      <td>1.0</td>\n",
    400        "      <td>0.0</td>\n",
    401        "      <td>21.645052</td>\n",
    402        "      <td>31.234535</td>\n",
    403        "    </tr>\n",
    404        "    <tr>\n",
    405        "      <th>1094</th>\n",
    406        "      <td>1.0</td>\n",
    407        "      <td>1.0</td>\n",
    408        "      <td>1.0</td>\n",
    409        "      <td>1.0</td>\n",
    410        "      <td>1.0</td>\n",
    411        "      <td>1.0</td>\n",
    412        "      <td>2.0</td>\n",
    413        "      <td>0.0</td>\n",
    414        "      <td>1.0</td>\n",
    415        "      <td>0.0</td>\n",
    416        "      <td>1.0</td>\n",
    417        "      <td>9.847456</td>\n",
    418        "      <td>19.954227</td>\n",
    419        "    </tr>\n",
    420        "  </tbody>\n",
    421        "</table>\n",
    422        "<p>1095 rows × 13 columns</p>\n",
    423        "</div>"
    424       ],
    425       "text/plain": [
    426        "      Window 1  Window 2  Window 3  Window 4  Heat Control 1  Heat Control 2  \\\n",
    427        "0          1.0       1.0       0.0       0.0             1.0             5.0   \n",
    428        "1          0.0       0.0       0.0       1.0             3.0             4.0   \n",
    429        "2          1.0       1.0       0.0       1.0             5.0             5.0   \n",
    430        "3          0.0       1.0       0.0       0.0             3.0             1.0   \n",
    431        "4          1.0       1.0       1.0       0.0             2.0             2.0   \n",
    432        "...        ...       ...       ...       ...             ...             ...   \n",
    433        "1090       0.0       0.0       1.0       1.0             0.0             0.0   \n",
    434        "1091       1.0       1.0       1.0       0.0             5.0             0.0   \n",
    435        "1092       1.0       1.0       1.0       0.0             4.0             2.0   \n",
    436        "1093       0.0       0.0       1.0       1.0             4.0             2.0   \n",
    437        "1094       1.0       1.0       1.0       1.0             1.0             1.0   \n",
    438        "\n",
    439        "      Heat Control 3  Heat Control 4  Door 1  Door 2  Door 3  \\\n",
    440        "0                0.0             0.0     1.0     1.0     1.0   \n",
    441        "1                2.0             0.0     1.0     1.0     0.0   \n",
    442        "2                1.0             1.0     0.0     1.0     0.0   \n",
    443        "3                4.0             4.0     0.0     1.0     0.0   \n",
    444        "4                2.0             0.0     1.0     1.0     0.0   \n",
    445        "...              ...             ...     ...     ...     ...   \n",
    446        "1090             5.0             5.0     1.0     0.0     0.0   \n",
    447        "1091             2.0             2.0     0.0     1.0     1.0   \n",
    448        "1092             3.0             5.0     1.0     0.0     1.0   \n",
    449        "1093             5.0             5.0     0.0     1.0     0.0   \n",
    450        "1094             2.0             0.0     1.0     0.0     1.0   \n",
    451        "\n",
    452        "      Temperature Outside  Temperature Bed  \n",
    453        "0                8.314993        17.260793  \n",
    454        "1                7.422077        16.479440  \n",
    455        "2                3.131294        13.649173  \n",
    456        "3               19.621818        27.223802  \n",
    457        "4               19.382874        23.714690  \n",
    458        "...                   ...              ...  \n",
    459        "1090            -2.980819         3.779726  \n",
    460        "1091             6.322275        17.002934  \n",
    461        "1092            -1.224444        13.168637  \n",
    462        "1093            21.645052        31.234535  \n",
    463        "1094             9.847456        19.954227  \n",
    464        "\n",
    465        "[1095 rows x 13 columns]"
    466       ]
    467      },
    468      "execution_count": 3,
    469      "metadata": {},
    470      "output_type": "execute_result"
    471     }
    472    ],
    473    "source": [
    474     "data_train_Temperature"
    475    ]
    476   },
    477   {
    478    "cell_type": "code",
    479    "execution_count": null,
    480    "metadata": {},
    481    "outputs": [],
    482    "source": []
    483   },
    484   {
    485    "cell_type": "markdown",
    486    "metadata": {},
    487    "source": [
    488     "Let us look at this closely"
    489    ]
    490   },
    491   {
    492    "cell_type": "code",
    493    "execution_count": 4,
    494    "metadata": {},
    495    "outputs": [
    496     {
    497      "data": {
    498       "text/html": [
    499        "<div>\n",
    500        "<style scoped>\n",
    501        "    .dataframe tbody tr th:only-of-type {\n",
    502        "        vertical-align: middle;\n",
    503        "    }\n",
    504        "\n",
    505        "    .dataframe tbody tr th {\n",
    506        "        vertical-align: top;\n",
    507        "    }\n",
    508        "\n",
    509        "    .dataframe thead th {\n",
    510        "        text-align: right;\n",
    511        "    }\n",
    512        "</style>\n",
    513        "<table border=\"1\" class=\"dataframe\">\n",
    514        "  <thead>\n",
    515        "    <tr style=\"text-align: right;\">\n",
    516        "      <th></th>\n",
    517        "      <th>Window 1</th>\n",
    518        "      <th>Window 2</th>\n",
    519        "      <th>Window 3</th>\n",
    520        "      <th>Window 4</th>\n",
    521        "      <th>Heat Control 1</th>\n",
    522        "      <th>Heat Control 2</th>\n",
    523        "      <th>Heat Control 3</th>\n",
    524        "      <th>Heat Control 4</th>\n",
    525        "      <th>Door 1</th>\n",
    526        "      <th>Door 2</th>\n",
    527        "      <th>Door 3</th>\n",
    528        "      <th>Temperature Outside</th>\n",
    529        "      <th>Temperature Bed</th>\n",
    530        "    </tr>\n",
    531        "  </thead>\n",
    532        "  <tbody>\n",
    533        "    <tr>\n",
    534        "      <th>count</th>\n",
    535        "      <td>1095.000000</td>\n",
    536        "      <td>1095.000000</td>\n",
    537        "      <td>1095.000000</td>\n",
    538        "      <td>1095.000000</td>\n",
    539        "      <td>1095.000000</td>\n",
    540        "      <td>1095.000000</td>\n",
    541        "      <td>1095.000000</td>\n",
    542        "      <td>1095.000000</td>\n",
    543        "      <td>1095.000000</td>\n",
    544        "      <td>1095.000000</td>\n",
    545        "      <td>1095.000000</td>\n",
    546        "      <td>1095.000000</td>\n",
    547        "      <td>1095.000000</td>\n",
    548        "    </tr>\n",
    549        "    <tr>\n",
    550        "      <th>mean</th>\n",
    551        "      <td>0.515982</td>\n",
    552        "      <td>0.523288</td>\n",
    553        "      <td>0.519635</td>\n",
    554        "      <td>0.490411</td>\n",
    555        "      <td>2.518721</td>\n",
    556        "      <td>2.463014</td>\n",
    557        "      <td>2.585388</td>\n",
    558        "      <td>2.528767</td>\n",
    559        "      <td>0.509589</td>\n",
    560        "      <td>0.499543</td>\n",
    561        "      <td>0.518721</td>\n",
    562        "      <td>8.572088</td>\n",
    563        "      <td>19.852056</td>\n",
    564        "    </tr>\n",
    565        "    <tr>\n",
    566        "      <th>std</th>\n",
    567        "      <td>0.499973</td>\n",
    568        "      <td>0.499686</td>\n",
    569        "      <td>0.499843</td>\n",
    570        "      <td>0.500136</td>\n",
    571        "      <td>1.716509</td>\n",
    572        "      <td>1.668685</td>\n",
    573        "      <td>1.702178</td>\n",
    574        "      <td>1.733328</td>\n",
    575        "      <td>0.500136</td>\n",
    576        "      <td>0.500228</td>\n",
    577        "      <td>0.499878</td>\n",
    578        "      <td>7.898873</td>\n",
    579        "      <td>6.926361</td>\n",
    580        "    </tr>\n",
    581        "    <tr>\n",
    582        "      <th>min</th>\n",
    583        "      <td>0.000000</td>\n",
    584        "      <td>0.000000</td>\n",
    585        "      <td>0.000000</td>\n",
    586        "      <td>0.000000</td>\n",
    587        "      <td>0.000000</td>\n",
    588        "      <td>0.000000</td>\n",
    589        "      <td>0.000000</td>\n",
    590        "      <td>0.000000</td>\n",
    591        "      <td>0.000000</td>\n",
    592        "      <td>0.000000</td>\n",
    593        "      <td>0.000000</td>\n",
    594        "      <td>-4.993865</td>\n",
    595        "      <td>0.590713</td>\n",
    596        "    </tr>\n",
    597        "    <tr>\n",
    598        "      <th>25%</th>\n",
    599        "      <td>0.000000</td>\n",
    600        "      <td>0.000000</td>\n",
    601        "      <td>0.000000</td>\n",
    602        "      <td>0.000000</td>\n",
    603        "      <td>1.000000</td>\n",
    604        "      <td>1.000000</td>\n",
    605        "      <td>1.000000</td>\n",
    606        "      <td>1.000000</td>\n",
    607        "      <td>0.000000</td>\n",
    608        "      <td>0.000000</td>\n",
    609        "      <td>0.000000</td>\n",
    610        "      <td>1.586682</td>\n",
    611        "      <td>14.603950</td>\n",
    612        "    </tr>\n",
    613        "    <tr>\n",
    614        "      <th>50%</th>\n",
    615        "      <td>1.000000</td>\n",
    616        "      <td>1.000000</td>\n",
    617        "      <td>1.000000</td>\n",
    618        "      <td>0.000000</td>\n",
    619        "      <td>3.000000</td>\n",
    620        "      <td>2.000000</td>\n",
    621        "      <td>3.000000</td>\n",
    622        "      <td>2.000000</td>\n",
    623        "      <td>1.000000</td>\n",
    624        "      <td>0.000000</td>\n",
    625        "      <td>1.000000</td>\n",
    626        "      <td>8.509676</td>\n",
    627        "      <td>20.950144</td>\n",
    628        "    </tr>\n",
    629        "    <tr>\n",
    630        "      <th>75%</th>\n",
    631        "      <td>1.000000</td>\n",
    632        "      <td>1.000000</td>\n",
    633        "      <td>1.000000</td>\n",
    634        "      <td>1.000000</td>\n",
    635        "      <td>4.000000</td>\n",
    636        "      <td>4.000000</td>\n",
    637        "      <td>4.000000</td>\n",
    638        "      <td>4.000000</td>\n",
    639        "      <td>1.000000</td>\n",
    640        "      <td>1.000000</td>\n",
    641        "      <td>1.000000</td>\n",
    642        "      <td>15.309044</td>\n",
    643        "      <td>25.284787</td>\n",
    644        "    </tr>\n",
    645        "    <tr>\n",
    646        "      <th>max</th>\n",
    647        "      <td>1.000000</td>\n",
    648        "      <td>1.000000</td>\n",
    649        "      <td>1.000000</td>\n",
    650        "      <td>1.000000</td>\n",
    651        "      <td>5.000000</td>\n",
    652        "      <td>5.000000</td>\n",
    653        "      <td>5.000000</td>\n",
    654        "      <td>5.000000</td>\n",
    655        "      <td>1.000000</td>\n",
    656        "      <td>1.000000</td>\n",
    657        "      <td>1.000000</td>\n",
    658        "      <td>21.992202</td>\n",
    659        "      <td>33.882457</td>\n",
    660        "    </tr>\n",
    661        "  </tbody>\n",
    662        "</table>\n",
    663        "</div>"
    664       ],
    665       "text/plain": [
    666        "          Window 1     Window 2     Window 3     Window 4  Heat Control 1  \\\n",
    667        "count  1095.000000  1095.000000  1095.000000  1095.000000     1095.000000   \n",
    668        "mean      0.515982     0.523288     0.519635     0.490411        2.518721   \n",
    669        "std       0.499973     0.499686     0.499843     0.500136        1.716509   \n",
    670        "min       0.000000     0.000000     0.000000     0.000000        0.000000   \n",
    671        "25%       0.000000     0.000000     0.000000     0.000000        1.000000   \n",
    672        "50%       1.000000     1.000000     1.000000     0.000000        3.000000   \n",
    673        "75%       1.000000     1.000000     1.000000     1.000000        4.000000   \n",
    674        "max       1.000000     1.000000     1.000000     1.000000        5.000000   \n",
    675        "\n",
    676        "       Heat Control 2  Heat Control 3  Heat Control 4       Door 1  \\\n",
    677        "count     1095.000000     1095.000000     1095.000000  1095.000000   \n",
    678        "mean         2.463014        2.585388        2.528767     0.509589   \n",
    679        "std          1.668685        1.702178        1.733328     0.500136   \n",
    680        "min          0.000000        0.000000        0.000000     0.000000   \n",
    681        "25%          1.000000        1.000000        1.000000     0.000000   \n",
    682        "50%          2.000000        3.000000        2.000000     1.000000   \n",
    683        "75%          4.000000        4.000000        4.000000     1.000000   \n",
    684        "max          5.000000        5.000000        5.000000     1.000000   \n",
    685        "\n",
    686        "            Door 2       Door 3  Temperature Outside  Temperature Bed  \n",
    687        "count  1095.000000  1095.000000          1095.000000      1095.000000  \n",
    688        "mean      0.499543     0.518721             8.572088        19.852056  \n",
    689        "std       0.500228     0.499878             7.898873         6.926361  \n",
    690        "min       0.000000     0.000000            -4.993865         0.590713  \n",
    691        "25%       0.000000     0.000000             1.586682        14.603950  \n",
    692        "50%       0.000000     1.000000             8.509676        20.950144  \n",
    693        "75%       1.000000     1.000000            15.309044        25.284787  \n",
    694        "max       1.000000     1.000000            21.992202        33.882457  "
    695       ]
    696      },
    697      "execution_count": 4,
    698      "metadata": {},
    699      "output_type": "execute_result"
    700     }
    701    ],
    702    "source": [
    703     "data_train_Temperature.describe()"
    704    ]
    705   },
    706   {
    707    "cell_type": "markdown",
    708    "metadata": {},
    709    "source": [
    710     "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."
    711    ]
    712   },
    713   {
    714    "cell_type": "code",
    715    "execution_count": 5,
    716    "metadata": {
    717     "scrolled": false
    718    },
    719    "outputs": [
    720     {
    721      "data": {
    722       "image/png": "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\n",
    723       "text/plain": [
    724        "<Figure size 864x864 with 2 Axes>"
    725       ]
    726      },
    727      "metadata": {
    728       "needs_background": "light"
    729      },
    730      "output_type": "display_data"
    731     },
    732     {
    733      "data": {
    734       "text/plain": [
    735        "<Figure size 864x864 with 0 Axes>"
    736       ]
    737      },
    738      "metadata": {},
    739      "output_type": "display_data"
    740     },
    741     {
    742      "data": {
    743       "image/png": "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\n",
    744       "text/plain": [
    745        "<Figure size 416.875x360 with 6 Axes>"
    746       ]
    747      },
    748      "metadata": {
    749       "needs_background": "light"
    750      },
    751      "output_type": "display_data"
    752     },
    753     {
    754      "data": {
    755       "image/png": "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\n",
    756       "text/plain": [
    757        "<Figure size 440.125x360 with 6 Axes>"
    758       ]
    759      },
    760      "metadata": {
    761       "needs_background": "light"
    762      },
    763      "output_type": "display_data"
    764     },
    765     {
    766      "data": {
    767       "image/png": "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\n",
    768       "text/plain": [
    769        "<Figure size 411.875x360 with 6 Axes>"
    770       ]
    771      },
    772      "metadata": {
    773       "needs_background": "light"
    774      },
    775      "output_type": "display_data"
    776     }
    777    ],
    778    "source": [
    779     "corrMatrix = data_train_Temperature.corr()\n",
    780     "plt.figure(figsize = (12,12))\n",
    781     "palette = sn.diverging_palette(20, 220, n=256)\n",
    782     "sn.heatmap(corrMatrix, annot=False, cmap = palette, vmin = -1, vmax = 1)\n",
    783     "plt.show()\n",
    784     "\n",
    785     "plt.figure(figsize = (12,12))\n",
    786     "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Window 1')\n",
    787     "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Heat Control 1')\n",
    788     "sn.pairplot(data_train_Temperature, vars = ['Temperature Outside', 'Temperature Bed'], kind = 'scatter', hue='Door 1')\n",
    789     "plt.show()"
    790    ]
    791   },
    792   {
    793    "cell_type": "markdown",
    794    "metadata": {},
    795    "source": [
    796     "We do not have that many data points. We should therefore first reduce the dimensionality of the problem.\n",
    797     "\n",
    798     "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",
    799     "Then "
    800    ]
    801   },
    802   {
    803    "cell_type": "markdown",
    804    "metadata": {},
    805    "source": [
    806     "We predict on the first 80% of the data and then validate on the remaining 20%"
    807    ]
    808   },
    809   {
    810    "cell_type": "code",
    811    "execution_count": 6,
    812    "metadata": {},
    813    "outputs": [],
    814    "source": [
    815     "observations = data_train_Temperature.shape[0]\n",
    816     "simple_data_set = data_train_Temperature.copy().drop(range(int(0.2*observations)), axis = 0)\n",
    817     "\n",
    818     "def predict(data):\n",
    819     "    simple_test_set = data.copy()\n",
    820     "\n",
    821     "    #some parameters are more important to fit right than others. (In our case, window 1 and doors 1 and 2)\n",
    822     "    weights = np.ones(12)\n",
    823     "    weights[0]  = 10 # Window 1\n",
    824     "    weights[1]  = 1 # Window 2\n",
    825     "    weights[2]  = 1 # Window 3\n",
    826     "    weights[3]  = 10 # Window 4\n",
    827     "    weights[4]  = 1 # Heat 1\n",
    828     "    weights[5]  = 1 # Heat 2\n",
    829     "    weights[6]  = 1 # Heat 3\n",
    830     "    weights[7]  = 0 # Heat 4\n",
    831     "    weights[8]  = 10 # Door 1\n",
    832     "    weights[9]  = 10 # Door 2\n",
    833     "    weights[10] = 1 # Door 3\n",
    834     "    weights[11] = 1 # Temp Out \n",
    835     "\n",
    836     "    for k in range(simple_test_set.shape[0]):\n",
    837     "        value = 0;\n",
    838     "        totaldist = 0\n",
    839     "        \n",
    840     "        \n",
    841     "        for j in range(simple_data_set.values.shape[0]):\n",
    842     "            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",
    843     "            totaldist = totaldist + 1/(np.linalg.norm(weights*simple_data_set.values[j,:-1] - weights*simple_test_set.values[k,:-1]))**4\n",
    844     "        simple_test_set.values[k, -1] = np.max([value/totaldist, simple_data_set.values[j,-2]])\n",
    845     "    \n",
    846     "    \n",
    847     "    return simple_test_set"
    848    ]
    849   },
    850   {
    851    "cell_type": "markdown",
    852    "metadata": {},
    853    "source": [
    854     "Now we compute error on validation set:"
    855    ]
    856   },
    857   {
    858    "cell_type": "code",
    859    "execution_count": 7,
    860    "metadata": {},
    861    "outputs": [
    862     {
    863      "data": {
    864       "text/plain": [
    865        "3.2587996607699106"
    866       ]
    867      },
    868      "execution_count": 7,
    869      "metadata": {},
    870      "output_type": "execute_result"
    871     }
    872    ],
    873    "source": [
    874     "validation_set = data_train_Temperature.copy().drop(range(int(0.2*observations), observations), axis = 0)\n",
    875     "res = predict(validation_set)\n",
    876     "# root mean square error:\n",
    877     "np.linalg.norm(res.values[:,-1] - validation_set.values[:,-1])/np.sqrt(len(res.values[:,-1]))"
    878    ]
    879   },
    880   {
    881    "cell_type": "markdown",
    882    "metadata": {},
    883    "source": [
    884     "The algorithm, was not very sophisticated, nonetheless I came within an accuracy of 3.5 degrees. For me this seems acceptable. \n",
    885     "Maybe you can help Freezing Fritz even more?\n",
    886     "\n",
    887     "I will just store my prediction on the test set now:"
    888    ]
    889   },
    890   {
    891    "cell_type": "code",
    892    "execution_count": null,
    893    "metadata": {},
    894    "outputs": [],
    895    "source": [
    896     "#make prediction \n",
    897     "prediction = predict(data_test_Temperature)\n",
    898     "predicted_Temperatures = prediction.values[:,-1]\n",
    899     "    \n",
    900     "np.savetxt('PhilippPetersens_Temperature_prediction.csv', predicted_Temperatures, delimiter=',') "
    901    ]
    902   },
    903   {
    904    "cell_type": "markdown",
    905    "metadata": {},
    906    "source": [
    907     "# Prediction"
    908    ]
    909   },
    910   {
    911    "cell_type": "code",
    912    "execution_count": 153,
    913    "metadata": {},
    914    "outputs": [],
    915    "source": [
    916     "import keras\n",
    917     "from keras.models import Sequential\n",
    918     "from keras.layers import Dense, Activation\n",
    919     "\n",
    920     "from sklearn.preprocessing import StandardScaler"
    921    ]
    922   },
    923   {
    924    "cell_type": "code",
    925    "execution_count": 233,
    926    "metadata": {},
    927    "outputs": [],
    928    "source": [
    929     "X = data_train_Temperature.to_numpy()[:,:-1]\n",
    930     "y = data_train_Temperature.to_numpy()[:,-1]\n",
    931     "\n",
    932     "scaler = StandardScaler()\n",
    933     "scaler.fit(np.c_[X[:,-1], y])\n",
    934     "\n",
    935     "scaled = scaler.transform(np.c_[X[:,-1], y])\n",
    936     "X_1, y = scaled[:,:-1], scaled[:,-1]\n",
    937     "X = np.c_[X[:,:-1], X_1]\n",
    938     "\n",
    939     "X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.20, random_state=42)"
    940    ]
    941   },
    942   {
    943    "cell_type": "code",
    944    "execution_count": 234,
    945    "metadata": {},
    946    "outputs": [],
    947    "source": [
    948     "data_train_splited = pd.DataFrame(np.c_[X_train, y_train], columns=data_train_Temperature.keys())\n",
    949     "\n",
    950     "X_bedopen = data_train_bedopen.to_numpy()[:,:-1]\n",
    951     "y_bedopen = data_train_bedopen.to_numpy()[:,-1]\n",
    952     "X_train_bedopen, X_valid_bedopen, y_train_bedopen, y_valid_bedopen = train_test_split(X_bedopen, y_bedopen, test_size=0.20, random_state=42)\n",
    953     "\n",
    954     "data_train_bedclosed = data_train_Temperature[ (data_train_Temperature['Door 1']==1) | (data_train_Temperature['Door 2']==1) ]\n",
    955     "X_bedclosed = data_train_bedclosed.to_numpy()[:,:-1]\n",
    956     "y_bedclosed = data_train_bedclosed.to_numpy()[:,-1]\n",
    957     "X_train_bedclosed, X_valid_bedclosed, y_train_bedclosed, y_valid_bedclosed = train_test_split(X_bedclosed, y_bedclosed, test_size=0.20, random_state=42)\n",
    958     "\n",
    959     "data_train_H1off = data_train_Temperature[ data_train_Temperature['Heat Control 1']==0 ]\n",
    960     "X_H1off = data_train_H1off.to_numpy()[:,:-1]\n",
    961     "y_H1off = data_train_H1off.to_numpy()[:,-1]\n",
    962     "X_train_H1off, X_valid_H1off, y_train_H1off, y_valid_H1off = train_test_split(X_H1off, y_H1off, test_size=0.20, random_state=42)\n",
    963     "\n",
    964     "data_train_H1on = data_train_Temperature[ data_train_Temperature['Heat Control 1']>0 ]\n",
    965     "X_H1on = data_train_H1on.to_numpy()[:,:-1]\n",
    966     "y_H1on = data_train_H1on.to_numpy()[:,-1]\n",
    967     "X_train_H1on, X_valid_H1on, y_train_H1on, y_valid_H1on = train_test_split(X_H1on, y_H1on, test_size=0.20, random_state=42)"
    968    ]
    969   },
    970   {
    971    "cell_type": "code",
    972    "execution_count": 168,
    973    "metadata": {},
    974    "outputs": [],
    975    "source": [
    976     "def train_with_keras(data_train=[X_train, y_train]):\n",
    977     "    model = Sequential()\n",
    978     "    model.add(Dense(2000, input_dim = X_train.shape[1], activation='relu'))\n",
    979     "    model.add(Dense(1))\n",
    980     "    model.compile(loss='mae', optimizer=keras.optimizers.adam_v2.Adam(learning_rate=0.001), metrics=['mse'])\n",
    981     "    history = model.fit(X_train, y_train, epochs=300, verbose=False)\n",
    982     "    return model\n",
    983     "\n",
    984     "def checkerror(y, pred):\n",
    985     "    print(np.linalg.norm(pred - y)/np.sqrt(len(y)))"
    986    ]
    987   },
    988   {
    989    "cell_type": "code",
    990    "execution_count": 230,
    991    "metadata": {},
    992    "outputs": [],
    993    "source": [
    994     "model = train_with_keras(data_train=[X_train, y_train])"
    995    ]
    996   },
    997   {
    998    "cell_type": "code",
    999    "execution_count": 231,
   1000    "metadata": {},
   1001    "outputs": [
   1002     {
   1003      "name": "stdout",
   1004      "output_type": "stream",
   1005      "text": [
   1006       "1.1216165292762097\n"
   1007      ]
   1008     }
   1009    ],
   1010    "source": [
   1011     "checkerror(scaler.inverse_transform(np.c_[X_valid[:,-1], y_valid])[:,-1],\\\n",
   1012     "           scaler.inverse_transform(np.c_[X_valid[:,-1], model.predict(X_valid).T[0]])[:,-1])"
   1013    ]
   1014   },
   1015   {
   1016    "cell_type": "code",
   1017    "execution_count": 237,
   1018    "metadata": {},
   1019    "outputs": [],
   1020    "source": [
   1021     "model_bedopen = train_with_keras(data_train=[X_train_bedopen, y_train_bedopen])\n",
   1022     "model_bedclosed = train_with_keras(data_train=[X_train_bedclosed, y_train_bedopen])"
   1023    ]
   1024   },
   1025   {
   1026    "cell_type": "code",
   1027    "execution_count": 247,
   1028    "metadata": {},
   1029    "outputs": [],
   1030    "source": [
   1031     "index_bed = list(data_train_Temperature.keys()).index('Door 1')\n",
   1032     "y_pred = []\n",
   1033     "for i in range(len(X_valid)):\n",
   1034     "    if X_valid[i][index_bed] == 0:\n",
   1035     "        y_pred.append(model.predict(np.reshape(X_valid[i], (1, 12)))[0, 0])\n",
   1036     "    if X_valid[i][index_bed] == 1:\n",
   1037     "        y_pred.append(model.predict(np.reshape(X_valid[i], (1, 12)))[0, 0])"
   1038    ]
   1039   },
   1040   {
   1041    "cell_type": "code",
   1042    "execution_count": 249,
   1043    "metadata": {},
   1044    "outputs": [
   1045     {
   1046      "name": "stdout",
   1047      "output_type": "stream",
   1048      "text": [
   1049       "1.1216166493882591\n"
   1050      ]
   1051     }
   1052    ],
   1053    "source": [
   1054     "checkerror(scaler.inverse_transform(np.c_[X_valid[:,-1], y_valid])[:,-1],\\\n",
   1055     "           scaler.inverse_transform(np.c_[X_valid[:,-1], y_pred])[:,-1])"
   1056    ]
   1057   },
   1058   {
   1059    "cell_type": "code",
   1060    "execution_count": null,
   1061    "metadata": {},
   1062    "outputs": [],
   1063    "source": []
   1064   },
   1065   {
   1066    "cell_type": "code",
   1067    "execution_count": null,
   1068    "metadata": {
   1069     "scrolled": false
   1070    },
   1071    "outputs": [],
   1072    "source": [
   1073     "prediction = model.predict(data_test_Temperature.iloc[:,:-1])\n",
   1074     "np.savetxt('my_Temperature_prediction.csv', prediction, delimiter=',') "
   1075    ]
   1076   },
   1077   {
   1078    "cell_type": "code",
   1079    "execution_count": 8,
   1080    "metadata": {},
   1081    "outputs": [
   1082     {
   1083      "ename": "NameError",
   1084      "evalue": "name 'y_train' is not defined",
   1085      "output_type": "error",
   1086      "traceback": [
   1087       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
   1088       "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
   1089       "Input \u001b[0;32mIn [8]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m fig, ax \u001b[38;5;241m=\u001b[39m plt\u001b[38;5;241m.\u001b[39msubplots(\u001b[38;5;241m3\u001b[39m, \u001b[38;5;241m2\u001b[39m, figsize\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m15\u001b[39m])\n\u001b[0;32m----> 2\u001b[0m ax[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mhist(\u001b[43my_train\u001b[49m)\n\u001b[1;32m      3\u001b[0m ax[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset_title(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124my_train\u001b[39m\u001b[38;5;124m'\u001b[39m, c\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mwhite\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m      4\u001b[0m ax[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m1\u001b[39m]\u001b[38;5;241m.\u001b[39mhist(model\u001b[38;5;241m.\u001b[39mpredict(X_train))\n",
   1090       "\u001b[0;31mNameError\u001b[0m: name 'y_train' is not defined"
   1091      ]
   1092     },
   1093     {
   1094      "data": {
   1095       "image/png": "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\n",
   1096       "text/plain": [
   1097        "<Figure size 720x1080 with 6 Axes>"
   1098       ]
   1099      },
   1100      "metadata": {
   1101       "needs_background": "light"
   1102      },
   1103      "output_type": "display_data"
   1104     }
   1105    ],
   1106    "source": [
   1107     "fig, ax = plt.subplots(3, 2, figsize=[10, 15])\n",
   1108     "ax[0][0].hist(y_train)\n",
   1109     "ax[0][0].set_title('y_train', c='white')\n",
   1110     "ax[0][1].hist(model.predict(X_train))\n",
   1111     "ax[0][1].set_title('y_train prediction', c='white')\n",
   1112     "\n",
   1113     "ax[1][0].hist(y_valid)\n",
   1114     "ax[1][0].set_title('y_valid', c='white')\n",
   1115     "ax[1][1].hist(model.predict(X_valid))\n",
   1116     "ax[1][1].set_title('y_valid prediction', c='white')\n",
   1117     "\n",
   1118     "ax[2][0].hist(data_test_Temperature.iloc[:,-1])\n",
   1119     "ax[2][0].set_title('y_test', c='white')\n",
   1120     "ax[2][1].hist(model.predict(data_test_Temperature.iloc[:,:-1]))\n",
   1121     "ax[2][1].set_title('y_test prediction', c='white')"
   1122    ]
   1123   },
   1124   {
   1125    "cell_type": "code",
   1126    "execution_count": null,
   1127    "metadata": {},
   1128    "outputs": [],
   1129    "source": []
   1130   },
   1131   {
   1132    "cell_type": "code",
   1133    "execution_count": null,
   1134    "metadata": {},
   1135    "outputs": [],
   1136    "source": []
   1137   }
   1138  ],
   1139  "metadata": {
   1140   "kernelspec": {
   1141    "display_name": "Python 3 (ipykernel)",
   1142    "language": "python",
   1143    "name": "python3"
   1144   },
   1145   "language_info": {
   1146    "codemirror_mode": {
   1147     "name": "ipython",
   1148     "version": 3
   1149    },
   1150    "file_extension": ".py",
   1151    "mimetype": "text/x-python",
   1152    "name": "python",
   1153    "nbconvert_exporter": "python",
   1154    "pygments_lexer": "ipython3",
   1155    "version": "3.10.4"
   1156   }
   1157  },
   1158  "nbformat": 4,
   1159  "nbformat_minor": 2
   1160 }
	mlearn Mathematics of Machine Learning
	git clone git://popovic.xyz/mlearn.git
	Log \| Files \| Refs