commit ad1d58884a0420f44ac1db1746970678c8130446
parent 690691e3e4d64cfda36454586d42d7a4d6737455
Author: miksa234 <milutin@popovic.xyz>
Date: Tue, 5 Apr 2022 13:55:31 +0200
samll fix
Diffstat:
3 files changed, 88 insertions(+), 94 deletions(-)
diff --git a/ass01/.ipynb_checkpoints/Analysis of Mystery Machine-checkpoint.ipynb b/ass01/.ipynb_checkpoints/Analysis of Mystery Machine-checkpoint.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 70,
+ "execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
@@ -15,8 +15,8 @@
"\n",
"from scipy.optimize import curve_fit\n",
"\n",
- "import sklearn.neighbors as neighbors\n",
- "from sklearn.model_selection import train_test_split"
+ "from sklearn.model_selection import train_test_split\n",
+ "from sklearn.tree import DecisionTreeClassifier "
]
},
{
@@ -33,7 +33,7 @@
},
{
"cell_type": "code",
- "execution_count": 71,
+ "execution_count": 30,
"metadata": {
"scrolled": true
},
@@ -254,7 +254,7 @@
"[5 rows x 100 columns]"
]
},
- "execution_count": 71,
+ "execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
@@ -281,7 +281,7 @@
},
{
"cell_type": "code",
- "execution_count": 72,
+ "execution_count": 31,
"metadata": {},
"outputs": [
{
@@ -600,7 +600,7 @@
"[8 rows x 100 columns]"
]
},
- "execution_count": 72,
+ "execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
@@ -618,7 +618,7 @@
},
{
"cell_type": "code",
- "execution_count": 73,
+ "execution_count": 32,
"metadata": {},
"outputs": [
{
@@ -655,7 +655,7 @@
},
{
"cell_type": "code",
- "execution_count": 74,
+ "execution_count": 33,
"metadata": {},
"outputs": [
{
@@ -664,7 +664,7 @@
"Text(0.5, 1.0, 'Distribution of min value--- not running')"
]
},
- "execution_count": 74,
+ "execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
@@ -756,7 +756,7 @@
},
{
"cell_type": "code",
- "execution_count": 75,
+ "execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
@@ -779,7 +779,7 @@
},
{
"cell_type": "code",
- "execution_count": 76,
+ "execution_count": 35,
"metadata": {},
"outputs": [
{
@@ -788,7 +788,7 @@
"Text(0.5, 1.0, 'Distribution of min value--- not running')"
]
},
- "execution_count": 76,
+ "execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
@@ -846,7 +846,7 @@
},
{
"cell_type": "code",
- "execution_count": 77,
+ "execution_count": 36,
"metadata": {},
"outputs": [
{
@@ -1271,7 +1271,7 @@
"[100 rows x 100 columns]"
]
},
- "execution_count": 77,
+ "execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
@@ -1282,7 +1282,7 @@
},
{
"cell_type": "code",
- "execution_count": 78,
+ "execution_count": 37,
"metadata": {
"scrolled": false
},
@@ -1329,7 +1329,7 @@
},
{
"cell_type": "code",
- "execution_count": 79,
+ "execution_count": 38,
"metadata": {},
"outputs": [
{
@@ -1338,7 +1338,7 @@
"Text(0.5, 1.0, 'Blue Switch On')"
]
},
- "execution_count": 79,
+ "execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
@@ -1367,7 +1367,7 @@
},
{
"cell_type": "code",
- "execution_count": 104,
+ "execution_count": 39,
"metadata": {},
"outputs": [
{
@@ -1376,7 +1376,7 @@
"[Text(0.5, 0, 'Blue Switch On'), Text(1.5, 0, 'Blue Switch Off')]"
]
},
- "execution_count": 104,
+ "execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
@@ -1421,7 +1421,7 @@
},
{
"cell_type": "code",
- "execution_count": 81,
+ "execution_count": 40,
"metadata": {},
"outputs": [
{
@@ -1453,7 +1453,7 @@
},
{
"cell_type": "code",
- "execution_count": 82,
+ "execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
@@ -1474,7 +1474,7 @@
},
{
"cell_type": "code",
- "execution_count": 83,
+ "execution_count": 42,
"metadata": {},
"outputs": [
{
@@ -1510,7 +1510,7 @@
},
{
"cell_type": "code",
- "execution_count": 84,
+ "execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
@@ -1541,7 +1541,7 @@
},
{
"cell_type": "code",
- "execution_count": 132,
+ "execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
@@ -1559,16 +1559,16 @@
},
{
"cell_type": "code",
- "execution_count": 133,
+ "execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "0.8668341708542714"
+ "0.8567839195979899"
]
},
- "execution_count": 133,
+ "execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
@@ -1600,7 +1600,7 @@
},
{
"cell_type": "code",
- "execution_count": 87,
+ "execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
@@ -1624,16 +1624,16 @@
},
{
"cell_type": "code",
- "execution_count": 88,
+ "execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "<matplotlib.collections.PathCollection at 0x7fe61badfa60>"
+ "<matplotlib.collections.PathCollection at 0x7f5b4054b010>"
]
},
- "execution_count": 88,
+ "execution_count": 47,
"metadata": {},
"output_type": "execute_result"
},
@@ -1662,7 +1662,7 @@
},
{
"cell_type": "code",
- "execution_count": 296,
+ "execution_count": 48,
"metadata": {},
"outputs": [
{
@@ -1672,15 +1672,12 @@
" min_samples_split=7, random_state=100)"
]
},
- "execution_count": 296,
+ "execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "from sklearn.ensemble import RandomForestClassifier\n",
- "from sklearn.tree import DecisionTreeClassifier \n",
- "from sklearn.model_selection import GridSearchCV\n",
"\n",
"dum2_train = data_train[data_train[:,1]==1]\n",
"d2_train = dum2_train[dum2_train[:,82] <= 3.5]\n",
@@ -1697,7 +1694,7 @@
},
{
"cell_type": "code",
- "execution_count": 297,
+ "execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
@@ -1725,7 +1722,7 @@
},
{
"cell_type": "code",
- "execution_count": 299,
+ "execution_count": 50,
"metadata": {},
"outputs": [
{
@@ -1755,18 +1752,18 @@
},
{
"cell_type": "code",
- "execution_count": 322,
+ "execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"X_test = np.array(data_test)[:,1:]\n",
"pred3 = predict(X_test, clf)\n",
- "np.savetxt('./prediction.txt', pred3, fmt='%1g')"
+ "np.savetxt('./prediction.csv', pred3, fmt='%1g', delimiter=',')"
]
},
{
"cell_type": "code",
- "execution_count": 321,
+ "execution_count": 54,
"metadata": {},
"outputs": [
{
@@ -1775,13 +1772,13 @@
"Text(0.5, 1.0, 'y_train')"
]
},
- "execution_count": 321,
+ "execution_count": 54,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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aOXOmIiMjdebMGe3atUvXX3+9vvrqK6f93nDDDfrggw+UkpKijh07KiAgQEOHDlVkZKTWrVunRx55RDfddJO+//57vfTSSwoODq7XyUAAANX31ltvqbi4uNJ67nY9e/ZUjx49tG/fPk2dOrVWPpNxCqhdFLEwnPj4eHXv3l1/+tOflJycLJvNpg4dOig8PNxRDEnSxIkTVV5erpSUFK1Zs0a9evXSxo0blZSUVOVntG/fXmlpaUpKStLrr78ui8Wi9u3b65ZbblGbNm0kXVqL7YknntDmzZv16KOPqry8XKtWrfrZInnFihXq0qWLXnnlFR06dEht27bVr3/9a82ZM6dWb6Otr8+53PLlyxUaGqrdu3crMTFRXl5e6tSpk8aMGaPw8HBJlyZ2+uKLL3Tw4EHl5eXJ19dXoaGhevTRR52K1KeeekpPPvmkVq9eLavVqvHjx1dZxB4+fFiHDx+Wp6enfH191aVLF91xxx2OExCXGz9+vPLz8/Xiiy/q/fffV/fu3bVkyRLl5uZW+uVgyZIlWr58udavX6+SkhINGTJEQ4cO1YwZM3T+/Hm99tprOnjwoEJCQrR27VodOHBAH330US1lFQBQF/bt2ydvb2+nx43+W2RkpLZt26bvvvuu0mSJNcE4BdQuD9uV7skEAAAAAMAN8UwsAAAAAMAwKGIBAAAAAIZRZRH7t7/9TZMmTVJYWJjMZrOioqL0xz/+UUVFRU79MjIyNH78eEef1NTUK+4vJSVFkZGR6t+/v+Li4vTBBx/UzpEAAAAAABq9KovYwsJCDR48WE888YSef/55TZ06Va+88ormzp3r6PPJJ59o1qxZ6tu3r7Zu3aq4uDitXLlSL774otO+UlJSlJiYqMmTJ2vz5s3q0aOHZsyYoa+//rr2jwwAAAAA0OjUaGKnP//5z1q+fLkyMzPVoUMH/eY3v1FhYaHS0tIcfR599FG9/fbbyszMlKenp6xWq26++WbdfffdeuSRRyRdWkMyNjZWISEhLs0YCwAAAABo2mr0TKx9iZGysjJZrVYdPnxYY8eOdeoTExOjvLw8HTlyRNKlBZaLiooUHR3t6OPl5aUxY8YoMzNTTJIMAAAAAKiKy+vElpeX6+LFizp69Kg2bNigyMhIdenSRceOHVNZWZl69uzp1D8kJESSlJOTI7PZrOzsbEmq1M++6PKZM2fUsWPHagX/448/qaLi2orftm19lZ9ffE37aArIk2vIk2vIk2vIU9VqK0eenh5q06ZlLUQExub6Q55cQ55cQ55cQ56qVh9js8tFbFhYmGMyp+HDhyshIUHSpWdmJcnf39+pv/21fbvFYpHJZJKPj49Tv1atWkmSCgoKql3EVlTYrnmgtO8HVSNPriFPriFPriFPVSNH7oWxuX6RJ9eQJ9eQJ9eQp6rVdY5cLmJTU1N1/vx5HT16VMnJyfrd736n7du312VsVWrb1rdW9hMY6Fcr+2nsyJNryJNryJNryFPVyBEAAE2Ly0Vs3759JUmDBg1Sv379dOedd+qNN95QcHCwpEtXWi9nf22/0urv7y+r1arS0lI1b97c0c9+pbZ169bVDj4/v/iaq/zAQD/l5RVV3bGJI0+uIU+uIU+uIU9Vq60ceXp61NqJUQAAULdqNLFT37595enpqdzcXHXr1k3e3t7Kyclx6nPs2DFJUlBQkKT/PAtrfzbWLjs7Wy1btlSHDh1qEgoAAAAAoAmpURH7ySefqKKiQl26dJHJZFJ4eLjS09Od+uzfv1+BgYHq16+fpEtXcP38/HTgwAFHn/LycqWnp2v48OHy8PC4hsMAAAAAADQFVd5OHB8fr/DwcIWEhKh58+b66quvlJKSot69eysqKkqSNHv2bE2ZMkXLli1TbGyssrKylJaWpuXLl8vT81KdbDKZNHPmTCUmJiogIEChoaFKS0tTbm6uY5IoAAAAAACupsoi1mw2a9++fTp58qQkqUuXLrrnnnt0//33y2QySZIGDhyojRs3au3atdq7d6/at2+vJUuWaNKkSU77io+Pl3RpkqizZ88qJCREW7ZsUZ8+fWr7uAAAMKTjx48rJSVFn332mY4ePaqgoCDt37/fsb28vFzbtm1TRkaGjh07pvLycvXq1UsPPPCAhg4dWml/KSkp2rlzp86ePavg4GAtXLiwUr/i4mKtWbNGf/3rX2W1WhUWFqZly5apS5cudX68AABUl4fNZjPsHNFM7FR/yJNryJNryJNryFPVGuPETm+++aaeeOIJDRgwQN99951sNptTEfvTTz8pIiJCd9xxh4YNG6ZmzZrp1Vdf1YEDB5ScnKyRI0c6+qakpCgxMVHz5s1z3AH1xhtvKC0tzekE8m9/+1sdOXJEixcvlq+vr5577jlZLBa99tpruu6666oVP2Nz/SFPriFPriFPriFPVauPsdnl2YkBAEDdi4yMdDyus3jxYn355ZdO2318fPTWW285Zv+XpFtuuUXff/+9tm3b5ihirVarkpOTNXXqVMedUEOGDFFsbKySk5OVlJQkSfrss8/0zjvvaMuWLYqIiJAk9erVS6NGjdKePXs0efLkOj9mAACqo8kXsdaycrdbY/BC6UUVWc43dBgAgAZgn0vi53h5eTkVsJLk4eGhPn366OOPP3a0ZWVlqaioSNHR0U7vHTNmjLZt2yabzSYPDw9lZGTIz89Pw4cPd/Tr1KmTBg0apMzMzAYpYhmbAQBX0+SLWJO3l2Ln/6Whw3DyWsI4cZMCAMBVFRUV+uSTTxzL2Un/WdLu8jZJCg4OVklJic6cOaOOHTsqOztbQUFBlYrn4OBgvfvuu3Uf/BUwNgMArqbJF7EAABhdamqqvvvuOz3xxBOONovFIpPJJB8fH6e+9qu4BQUF6tixoywWi/z8Kl/19Pf3V2FhYbVjcZdni+uCu10dltwzJndEnlxDnlxDnqpW1zmiiAUAwMA++ugjPf300/r1r3+tm266qaHDqbWJndyRu03mwgQzriFPriFPriFPVauPiZ2u/uANAABwW19//bVmzZqlqKgoLVy40Gmbv7+/rFarSktLndrtV1dbt27t6FdUVPmXDYvFUunZWwAA3AFFLAAABpSbm6vf/OY3Cg0N1Zo1a+Th4eG03f4srP3ZWLvs7Gy1bNlSHTp0cPSzL+VzuWPHjikoKKgOjwAAgJqhiAUAwGDy8vL061//Wu3atdPGjRtlMpkq9Rk0aJD8/Px04MABR1t5ebnS09M1fPhwR9EbEREhi8Wiv//9745+p0+fVlZWlkaMGFH3BwMAQDXxTCwAAG7k/PnzysjIkCSdOnVKxcXFOnjwoCTJbDarbdu2+s1vfqP8/HwtXrxYx44dc3r/jTfeKEkymUyaOXOmEhMTFRAQoNDQUKWlpSk3N1cJCQmO/gMGDNCtt96qpUuXavHixfL19VVSUpJ+8YtfKC4urn4OGgCAaqCIBQDAjeTn52vu3LlObfbXq1at0pAhQ/T1119LkmbPnl3p/d98843j7/Hx8ZIuzV589uxZhYSEaMuWLerTp4/TexISErRmzRo9/vjjslqtCgsLU1JSkq677rpaPTYAAGoDRSwAAG6kS5cuToXolVS1/XLx8fGOYvbn+Pr6asWKFVqxYoXL+wUAoKHwTCwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMKosYtPT0zVr1ixFREToxhtvVGxsrHbt2qWKigpHn8WLF6t3796V/hw8eLDS/lJSUhQZGan+/fsrLi5OH3zwQe0eEQAAAACg0WpWVYft27erU6dOeuSRR9S2bVt9+OGHeuqpp3TixAktWrTI0a9r16565plnnN7bo0cPp9cpKSlKTEzUvHnzFBoaqrS0NM2YMUNpaWnq06dP7RwRAAAAAKDRqrKI3bRpkwICAhyvw8PDVVJSop07d2revHkymUySJB8fH914440/ux+r1ark5GRNnTpV8fHxkqQhQ4YoNjZWycnJSkpKusZDAQAAAAA0dlXeTnx5AWvXt29flZaWqqCgwOUPysrKUlFRkaKjox1tXl5eGjNmjDIzM2Wz2VzeFwAAAACgaarRxE4ff/yxWrdurbZt2zracnNzddNNN6lfv3664447dODAAaf3ZGdnS5J69uzp1B4cHKySkhKdOXOmJqEAAAAAAJqQKm8n/m9ffPGF9uzZo9mzZ8vLy0vSpSuzZrNZwcHBKioq0ssvv6x58+bpwoULiouLkyRZLBaZTCb5+Pg47a9Vq1aSpIKCAnXs2LFasbRt61vd8A0jMNCvoUOoxB1jckfkyTXkyTXkqWrkCACApqVaRWxeXp7mzJkjs9ms6dOnO9qnTZvm1C8qKkpTp07VunXrHEVsXcjPL1ZFxbXdhuyuv/zk5RU1dAhOAgP93C4md0SeXEOeXEOeqlZbOfL09GjUJ0YBAGhMXL6duKioSNOnT5ePj4+Sk5Pl7e191f6jR4/WDz/8oHPnzkmS/P39ZbVaVVpa6tSvsLBQktS6detqhg4AAAAAaGpcKmJLS0s1c+ZM5efn6/nnn1ebNm2q/UH2Z2Htz8baZWdnq2XLlurQoUO19wkAQGNz/PhxLV++XOPGjVNoaKhiYmKu2C8jI0Pjx4+X2WxWVFSUUlNTr9jPlfXZi4uLtXz5coWFhWngwIH63e9+p5MnT9bqcQEAUFuqLGIvXryouXPn6ptvvtHWrVvVuXPnKndqs9mUnp6uzp07O2Y3HjRokPz8/JwmfCovL1d6erqGDx8uDw+PazgMAAAah6NHjyojI0Pdu3evNBmi3SeffKJZs2apb9++2rp1q+Li4rRy5Uq9+OKLTv3s67NPnjxZmzdvVo8ePTRjxgx9/fXXTv3mz5+vQ4cO6dFHH1ViYqL+/e9/67777tP58+fr7DgBAKipKp+JXbFihd5++20tXLhQFy5c0KeffurYFhwcrMLCQi1evFjR0dHq3r27LBaL0tLS9NFHH2nNmjWOviaTSTNnzlRiYqICAgIUGhqqtLQ05ebmKiEhoU4ODgAAo4mMjFRUVJQkafHixfryyy8r9dmwYYNCQ0O1cuVKSZfWcD99+rQ2bNigiRMnytPT0+X12T/77DO988472rJliyIiIiRJvXr10qhRo7Rnzx5Nnjy5Pg4bAACXVVnEvvvuu5Kkp59+utK2HTt2qHfv3vL19VVycrLy8/Pl7e2t0NBQJScnKzIy0qm/fRBNTU3V2bNnFRISoi1btqhPnz61cSwAABiep+fVb5KyWq06fPiw5s+f79QeExOjl156SUeOHJHZbL7q+uzbtm2TzWaTh4eHMjIy5Ofnp+HDhzv6derUSYMGDVJmZiZFLADA7VRZxB46dKjKnSQnJ7v8gfHx8Y5iFgAAVE9ubq7Kysoq3WocEhIiScrJyZHZbHZpffaOHTsqOztbQUFBlYrn4OBgx4lsAADcicuzEwMAgIZnn9Xf39/fqd3+2r7dlfXZ7f38/CovN+fv7+/YFwAA7qRa68QCAABcTWNeb9cd15Z3x5jcEXlyDXlyDXmqWl3niCIWAAADsV9JtVgsTu321/btl6/P3rx5c0e//16f3d/fX6dPn670ORaLxbGv6sjPL1ZFha3a77ucu/6CmJdX1NAhOAkM9HO7mNwReXINeXINeapabeXI09PjZ0+McjsxAAAG0q1bN3l7eysnJ8ep/dixY5KkoKAgSa6vz96zZ0999913stmcC89jx4459gUAgDuhiAUAwEBMJpPCw8OVnp7u1L5//34FBgaqX79+klxfnz0iIkIWi0V///vfHf1Onz6trKwsjRgxoh6OCACA6uF2YgAA3Mj58+eVkZEhSTp16pSKi4t18OBBSZLZbFbnzp01e/ZsTZkyRcuWLVNsbKyysrKUlpam5cuXO2YZdnV99gEDBujWW2/V0qVLtXjxYvn6+iopKUm/+MUvFBcXV/8JAACgChSxAAC4kfz8fM2dO9epzf561apViouL08CBA7Vx40atXbtWe/fuVfv27bVkyRJNmjTJ6X2urs+ekJCgNWvW6PHHH5fValVYWJiSkpJ03XXX1eGRAgBQMxSxAAC4kS5duuibb76psl9ERIQiIiKq7OfK+uy+vr5asWKFVqxY4XKcAAA0FJ6JBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDaNbQAQAAjMHP/zr5NHevYcNaVt7QIQAAgHrmXr+NAADclk/zZoqd/5eGDsPJawnjGjoEAABQz7idGAAAAABgGFUWsenp6Zo1a5YiIiJ04403KjY2Vrt27VJFRYVTv4yMDI0fP15ms1lRUVFKTU294v5SUlIUGRmp/v37Ky4uTh988EHtHAkAAAAAoNGrsojdvn27TCaTHnnkEW3atElRUVF66qmn9PTTTzv6fPLJJ5o1a5b69u2rrVu3Ki4uTitXrtSLL77otK+UlBQlJiZq8uTJ2rx5s3r06KEZM2bo66+/rv0jAwAAAAA0OlU+E7tp0yYFBAQ4XoeHh6ukpEQ7d+7UvHnzZDKZtGHDBoWGhmrlypWOPqdPn9aGDRs0ceJEeXp6ymq1Kjk5WVOnTlV8fLwkaciQIYqNjVVycrKSkpLq6BABAAAAAI1FlVdiLy9g7fr27avS0lIVFBTIarXq8OHDGjt2rFOfmJgY5eXl6ciRI5KkrKwsFRUVKTo62tHHy8tLY8aMUWZmpmw227UeCwAAAACgkavRxE4ff/yxWrdurbZt2yo3N1dlZWXq2bOnU5+QkBBJUk5OjiQpOztbkir1Cw4OVklJic6cOVOTUAAAAAAATUi1i9gvvvhCe/bs0bRp0+Tl5aXCwkJJkr+/v1M/+2v7dovFIpPJJB8fH6d+rVq1kiQVFBRUO3gAAAAAQNNSrXVi8/LyNGfOHJnNZk2fPr2uYnJZ27a+DR1CnQkM9GvoECpxx5jcEXlyDXlyDXmqGjkCAKBpcbmILSoq0vTp0+Xj46Pk5GR5e3tL+s+VVIvF4tTf/tq+3d/fX1arVaWlpWrevLmjn/1KbevWrasdfH5+sSoqru1ZWnf95Scvr6ihQ3ASGOjndjG5I/LkGvLkGnfLU2P+vvT09DDcidE333xTmzZtUnZ2tlq0aKFBgwZp/vz56tGjh1O/vXv3atOmTTp16pS6deum2bNnV5rHoqysTM8995xeffVVFRUVyWw2a+nSperbt289HhEAAK5x6Xbi0tJSzZw5U/n5+Xr++efVpk0bx7Zu3brJ29vb8eyr3bFjxyRJQUFBkv7zLKz92Vi77OxstWzZUh06dKj5UQAA0IR88MEHeuCBBxQUFKT169dr2bJlysnJ0f3336/i4mJHv4MHD2rRokUaNWqUtm7dqqFDh+rhhx9WRkaG0/5WrVqlnTt3as6cOdq4caO8vb113333MV8FAMAtVVnEXrx4UXPnztU333yjrVu3qnPnzk7bTSaTwsPDlZ6e7tS+f/9+BQYGql+/fpKkQYMGyc/PTwcOHHD0KS8vV3p6uoYPHy4PD4/aOB4AABq9/fv3q1OnTvrjH/+oYcOGacyYMVq1apV++OEHffzxx45+SUlJGj16tObPn6/w8HAtW7ZMN998s9atW+foc+bMGe3evVvz58/X3XffrWHDhjm2v/DCC/V+bAAAVKXKInbFihV6++239dvf/lYXLlzQp59+6vhjP9s7e/Zsffnll1q2bJk+/PBDJScnKy0tTbNnz5an56WPMJlMmjlzpv70pz9p27ZtOnz4sB555BHl5uZq5syZdXuUAAA0IhcvXlTLli2dTgD7+Tnf7n3ixAnl5OQ4LW0nXVoC74svvtC5c+ckSe+++67Ky8udbjH29fXVyJEjlZmZWYdHAQBAzVT5TOy7774rSXr66acrbduxY4fCwsI0cOBAbdy4UWvXrtXevXvVvn17LVmyRJMmTXLqHx8fL0lKTU3V2bNnFRISoi1btqhPnz61cSwAADQJ48eP1/79+5Wamqpx48bJYrHoj3/8o3r27KmhQ4dK+s8Sd1da2s6+PSAgQNnZ2WrXrp3To0L2fvv371dFRYXjhDQAAO6gyiL20KFDLu0oIiJCERERVfaLj493FLMAAKD6wsPDtW7dOi1YsEBPPvmkJKlXr17avn27TCaTJP3sEnj2CRcvXwLvv6/i2vuVlZWppKREvr7GmvQKANC4VWuJHQAA0PCysrK0aNEiTZgwQZGRkSooKNDGjRs1c+ZM7dq1q9Ka7PXJaLM8V4c7ztDtjjG5I/LkGvLkGvJUtbrOEUUsAAAG8+STTyosLEy///3vHW033nijbr31Vv3lL3/RxIkTnZbACwwMdPSzX4G9fAm8oqLKyxQVFhbK29tbLVq0qFZsLH9Xf9xtGS53RZ5cQ55cQ56qVls5utrydzzkAgCAwWRnZ1eaT6Jjx45q06aNcnNzJf1nibv/XgLPvtTd5Uvg5efnq6CgoFK/Hj168DwsAMDtcCUWAACD6dSpk44cOeLUdurUKf3444+OpfC6du2qoKAgHThwQKNGjXL0279/v8xmswICAiRJt9xyizw9PZWenu6YkPGnn37SoUOHdOedd9bTEQEAasLP/zr5NHevks5aVl7nn+FeRwwAAKo0efJkPfHEE3riiSd02223qaCgQMnJyWrbtq3GjBnj6DdnzhzNmzdP3bp1080336y33npL7733njZv3uzo06FDB91zzz165pln1KxZM3Xq1Enbtm2TJE2bNq3ejw0A4Dqf5s0UO/8vDR2Gk9cSxtX5Z1DEAgBgMJMnT5a3t7d27dqlPXv2qGXLlhowYICeffZZp6VyxowZowsXLmjTpk1KSUlRt27dlJCQUGk1gSVLlqhFixZ69tlnVVRUJLPZrO3bt6tDhw71fWgAAFSJIhYAAIPx8PDQxIkTNXHixCr7jh8/XuPHj79qH29vby1YsEALFiyorRABAKgzzNYAAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMNwqYg9fvy4li9frnHjxik0NFQxMTGV+ixevFi9e/eu9OfgwYOV+qakpCgyMlL9+/dXXFycPvjgg2s/EgAAAABAo9fMlU5Hjx5VRkaGBgwYoIqKCtlstiv269q1q5555hmnth49eji9TklJUWJioubNm6fQ0FClpaVpxowZSktLU58+fWp2FAAAAACAJsGlIjYyMlJRUVGSLl1x/fLLL6/Yz8fHRzfeeOPP7sdqtSo5OVlTp05VfHy8JGnIkCGKjY1VcnKykpKSqhk+AAAAAKApcel2Yk/P2nl0NisrS0VFRYqOjna0eXl5acyYMcrMzPzZK7wAAAAAAEi1PLFTbm6ubrrpJvXr10933HGHDhw44LQ9OztbktSzZ0+n9uDgYJWUlOjMmTO1GQ4AAAAAoJGptSK2b9++WrRokTZs2KCkpCR17NhR8+bN0549exx9LBaLTCaTfHx8nN7bqlUrSVJBQUFthQMAQKO3d+9excXFqX///goLC9P999+vc+fOObZnZGRo/PjxMpvNioqKUmpq6hX3w4SLAAAjcemZWFdMmzbN6XVUVJSmTp2qdevWKS4urrY+xknbtr51sl93EBjo19AhVOKOMbkj8uQa8uQa8lS1ppqj5ORkbdmyRTNmzNCiRYtUVFSkDz/8UGVlZZKkTz75RLNmzdK4ceO0aNEiZWVlaeXKlWrWrJkmTZrk2A8TLgIAjKbWitgrGT16tB5//HGdO3dOAQEB8vf3l9VqVWlpqZo3b+7oV1hYKElq3bp1tfafn1+siopre47WXX/5ycsraugQnAQG+rldTO6IPLmGPLnG3fLUmL8vPT09DHViNCcnR+vXr9f69es1cuRIR7t9EkZJ2rBhg0JDQ7Vy5UpJUnh4uE6fPq0NGzZo4sSJ8vT0ZMJFAIAh1eozsVWxPwtrfzbWLjs7Wy1btlSHDh3qMxwAAAxpz5496tSpk1MBezmr1arDhw9r7NixTu0xMTHKy8vTkSNHJDHhIgDAmOqsiLXZbEpPT1fnzp0VEBAgSRo0aJD8/PycJnwqLy9Xenq6hg8fLg8Pj7oKBwCARuOzzz5T7969tXHjRg0bNkz9+vXThAkT9NFHH0m6NNFiWVlZpYkUQ0JCJF26kisx4SIAwJhcup34/PnzysjIkCSdOnVKxcXFOnjwoCTJbDZLurR+bHR0tLp37y6LxaK0tDR99NFHWrNmjWM/JpNJM2fOVGJiogICAhzP3uTm5iohIaG2jw0AgEYpLy9PX375pb7++mstXbpUvr6+2rZtm37zm9/owIEDjsd0/P39nd5nf23f7sqEix07dqzrwwEAoFpcKmLz8/M1d+5cpzb761WrVikyMlK+vr5KTk5Wfn6+vL29FRoaquTkZEVGRjq9z/7MTWpqqs6ePauQkBBt2bKFySMAAHCRzWZTSUmJdu3apb59+0qSBg8erNtuu00pKSmKiYlpsNiM9Gxxdbnjc+HuGJM7Ik+uIU+uIU9Vq+scuVTEdunSRd98881V+yQnJ7v8ofHx8Y5iFgAAVI+/v79at27tKGAl6brrrtOAAQN09OhRx5VUi8Xi9D77a/v22p5wUWLSxfrkbpO/uSvy5Bry5Bp3y1Nj/r682qSL9TqxEwAAuHbBwcE/u620tFTdunWTt7e349lXu2PHjkmSgoKCJDHhIgDAmChiAQAwmJEjR6qgoMAxy7AklZSU6NNPP1W/fv1kMpkUHh6u9PR0p/ft379fgYGB6tevnyQmXAQAGFOdrhMLAABqX1RUlPr37685c+Zo3rx5atmypbZt26YLFy7o/vvvlyTNnj1bU6ZM0bJlyxQbG6usrCylpaVp+fLl8vS8dA6bCRcBAEZEEQsAgMF4enpq8+bNWrNmjR5//HGVlpZqwIAB2rFjh7p37y5JGjhwoDZu3Ki1a9dq7969at++vZYsWaJJkyY57YsJFwEARkMRCwCAAQUEBGj16tVX7RMREaGIiIgq98WEiwAAI+GZWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIbhUhF7/PhxLV++XOPGjVNoaKhiYmKu2C8jI0Pjx4+X2WxWVFSUUlNTr9gvJSVFkZGR6t+/v+Li4vTBBx/U/AgAAAAAAE2GS0Xs0aNHlZGRoe7du6tnz55X7PPJJ59o1qxZ6tu3r7Zu3aq4uDitXLlSL774olO/lJQUJSYmavLkydq8ebN69OihGTNm6Ouvv772owEAAAAANGrNXOkUGRmpqKgoSdLixYv15ZdfVuqzYcMGhYaGauXKlZKk8PBwnT59Whs2bNDEiRPl6ekpq9Wq5ORkTZ06VfHx8ZKkIUOGKDY2VsnJyUpKSqqt4wIAAAAANEIuXYn19Lx6N6vVqsOHD2vs2LFO7TExMcrLy9ORI0ckSVlZWSoqKlJ0dLSjj5eXl8aMGaPMzEzZbLbqxg8AQJP3008/acSIEerdu7e++OILp2179+7V6NGjZTabFR0drQMHDlR6f1lZmRISEnTLLbdowIABmjJlir766qv6Ch8AgGqplYmdcnNzVVZWVulW45CQEElSTk6OJCk7O1uSKvULDg5WSUmJzpw5UxvhAADQpKxfv17l5eWV2g8ePKhFixZp1KhR2rp1q4YOHaqHH35YGRkZTv1WrVqlnTt3as6cOdq4caO8vb113333MS4DANySS7cTV6WwsFCS5O/v79Ruf23fbrFYZDKZ5OPj49SvVatWkqSCggJ17NjR5c9t29a3xjG7u8BAv4YOoRJ3jMkdkSfXkCfXkKeqNfUcffvtt9q9e7cWL16s5cuXO21LSkrS6NGjNX/+fEmXHvXJycnRunXrFBERIUk6c+aMdu/eraVLl+ruu++WJA0YMEC33XabXnjhBT3yyCP1e0AAAFShVorYhpKfX6yKimu7Bdldf/nJyytq6BCcBAb6uV1M7og8uYY8ucbd8tSYvy89PT0Me2J0xYoVmjx5snr06OHUfuLECeXk5GjevHlO7TExMVqyZInOnTungIAAvfvuuyovL3d6JMjX11cjR45UZmYmRSwAwO3Uyu3E9iupFovFqd3+2r7d399fVqtVpaWlTv3sV2pbt25dG+EAANAk7N27V8ePH9fMmTMrbbM/ynOlR3gu356dna127dqpTZs2lfp9//33qqioqIvQAQCosVopYrt16yZvb2/HgGh37NgxSVJQUJCk/wyk9mdj7bKzs9WyZUt16NChNsIBAKDRKyoq0tNPP62FCxeqZcuWlbb/3KM+9hPLlz/q4+dX+Sp7q1atVFZWppKSktoOHQCAa1IrtxObTCaFh4crPT1d9913n6N9//79CgwMVL9+/SRJgwYNkp+fnw4cOKDQ0FBJUnl5udLT0zV8+HB5eHjURjgAADR6zz77rLp3765f/epXDR2KE6Pelu0Kd7yl3h1jckfkyTXkyTXkqWp1nSOXitjz5887ZjI8deqUiouLdfDgQUmS2WxW586dNXv2bE2ZMkXLli1TbGyssrKylJaWpuXLlzuW6DGZTJo5c6YSExMVEBCg0NBQpaWlKTc3VwkJCXV0iAAANC5Hjx7V7t27tW3bNsejO/YrpiUlJSouLnZ61CcwMNDxXvsV2Msf9SkqqvxccWFhoby9vdWiRYtqxcZ8FfXH3Z6bd1fkyTXkyTXulqfG/H15tfkqXCpi8/PzNXfuXKc2++tVq1YpLi5OAwcO1MaNG7V27Vrt3btX7du315IlSzRp0iSn98XHx0uSUlNTdfbsWYWEhGjLli3q06dPtQ8MAICm6Pjx47p48aKmTp1aadvUqVPVp08frV+/XtKlZ18vfy7W/kjP5Y/65Ofnq6CgwGluiuzsbPXo0aPKteIBAKhvLhWxXbp00TfffFNlv4iICMeU/VcTHx/vKGYBAED1DBo0SDt27HBq++qrr7Rq1So9/vjj6tevn7p27aqgoCAdOHBAo0aNcvTbv3+/zGazAgICJEm33HKLPD09lZ6e7jjx/NNPP+nQoUO688476++gAABwkaGX2AEAoCkKCAhQWFjYFbf169dPZrNZkjRnzhzNmzdP3bp1080336y33npL7733njZv3uzo36FDB91zzz165pln1KxZM3Xq1Enbtm2TJE2bNq3uDwYAgGqiiAUAoJEaM2aMLly4oE2bNiklJUXdunVTQkJCpbumlixZohYtWujZZ59VUVGRzGaztm/fzqoBAAC3RBELAEAjEBYWdsVHf8aPH6/x48df9b3e3t5asGCBFixYUFfhAQBQa5itAQAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGLVWxO7Zs0e9e/eu9GfFihVO/TIyMjR+/HiZzWZFRUUpNTW1tkIAAAAAADRyzWp7h88//7z8/Pwcr9u1a+f4+yeffKJZs2Zp3LhxWrRokbKysrRy5Uo1a9ZMkyZNqu1QAABolNLT0/Xaa6/pyJEjKiwsVNeuXTVp0iTdc8898vT8z/npjIwMPfvsszp27Jg6dOigadOm6d577620v5SUFO3cuVNnz55VcHCwFi5cqKFDh9bnIQEA4LJaL2L79eungICAK27bsGGDQkNDtXLlSklSeHi4Tp8+rQ0bNmjixIlOAy8AALiy7du3q1OnTnrkkUfUtm1bffjhh3rqqad04sQJLVq0SJLrJ45TUlKUmJioefPmKTQ0VGlpaZoxY4bS0tLUp0+fhjpEAAB+Vq0XsT/HarXq8OHDmj9/vlN7TEyMXnrpJR05ckRms7m+wgEAwLA2bdrkdMI4PDxcJSUl2rlzp+bNmyeTyeTSiWOr1ark5GRNnTpV8fHxkqQhQ4YoNjZWycnJSkpKapDjAwDgamr90mdsbKz69u2ryMhIrV+/XhcvXpQk5ebmqqysTD179nTqHxISIknKycmp7VAAAGiUrnTHU9++fVVaWqqCggLHieOxY8c69YmJiVFeXp6OHDkiScrKylJRUZGio6Mdfby8vDRmzBhlZmbKZrPV7YEAAFADtXYlNjAwUA8++KD69+8vLy8vZWZmauPGjTp58qRWr16twsJCSZK/v7/T++yv7duro21b32sP3E0FBvpV3ameuWNM7og8uYY8uYY8VY0cXfLxxx+rdevWatu2rb777rsqTxybzWZlZ2dLUqV+wcHBKikp0ZkzZ9SxY8f6OQAAAFxUa0Xs8OHDNXz4cMfrYcOGyc/PT+vWrdOsWbNq62Oc5OcXq6Li2s4Su+svP3l5RQ0dgpPAQD+3i8kdkSfXkCfXuFueGvP3paenh6FPjH7xxRfas2ePZs+eLS8vL5dPHFssFplMJvn4+Dj1a9WqlSSpoKCAIhYA4Hbq9JnYMWPGaN26dTpy5Ijj7K/FYnHqY39tHzABAIDr8vLyNGfOHJnNZk2fPr2hwzH0yYCquOOJHHeMyR2RJ9eQJ9eQp6rVdY7qbWKnbt26ydvbWzk5ORoxYoSj/dixY5KkoKCg+goFAIBGoaioSNOnT5ePj4+Sk5Pl7e0t6T8nhqs6cezv7y+r1arS0lI1b97c0c9+pbZ169bVjom7pOqPu92t4a7Ik2vIk2vcLU+N+fvyandJ1emaNq+//ro8PDx0ww03yGQyKTw8XOnp6U599u/fr8DAQPXr168uQwEAoFEpLS3VzJkzlZ+fr+eff15t2rRxbLv8xPHl/vvEsf1ZWPuzsXbZ2dlq2bKlOnToUJeHAABAjdTaldj4+HiFhYWpV69e8vDw0N///nft2rVLEyZMUNeuXSVJs2fP1pQpU7Rs2TLFxsYqKytLaWlpWr58OWvEAgDgoosXL2ru3Ln65ptvlJqaqs6dOzttv/zE8X333edo/+8Tx4MGDZKfn58OHDig0NBQSVJ5ebnS09M1fPhweXh41NsxAQDgqlorYoOCgvTKK6/ozJkzunjxonr06KEFCxZo2rRpjj4DBw7Uxo0btXbtWu3du1ft27fXkiVLnBZdBwAAV7dixQq9/fbbWrhwoS5cuKBPP/3UsS04OFi+vr4unTg2mUyaOXOmEhMTFRAQoNDQUKWlpSk3N1cJCQkNdHQAAFxdrRWxS5cu1dKlS6vsFxERoYiIiNr6WAAAmpx3331XkvT0009X2rZjxw6FhYW5fOI4Pj5ekpSamqqzZ88qJCREW7ZsUZ8+fer+QAAAqIF6m9gJAADUjkOHDrnUz9UTx/Hx8Y5iFgAAd8eDqAAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYRoMUsd9//73i4+M1cOBAhYeH64knntD58+cbIhQAACDGZgCAcTSr7w+0WCyaOnWqOnXqpKSkJJ07d06rVq3SuXPnlJiYWN/hAADQ5DE2AwCMpN6L2N27d8tisWjv3r0KCAiQJHl5eWnBggWaNWuWQkJC6jskAACaNMZmAICR1PvtxJmZmQoPD3cMkpJ0++23y2QyKTMzs77DAQCgyWNsBgAYSb0XsdnZ2QoODnZqM5lM6tatm3Jycuo7HAAAmjzGZgCAkTTIM7H+/v6V2v39/VVYWFitfXl6etRKTO3bXFcr+6lNtXVstckdY3JH5Mk15Mk17panxvp96W55rm+Mza5xx58Td4zJHZEn15An17hbnhrr9+XV9lHvRWxtatOmZa3sJ2XZL2tlP7WpbVvfhg6hEneMyR2RJ9eQJ9e4W574vkRVGJvrlzvG5I7Ik2vIk2vcLU9N8fuy3m8n9vf3l8ViqdRusVjUqlWr+g4HAIAmj7EZAGAk9V7E9uzZU9nZ2U5tVqtVubm5CgoKqu9wAABo8hibAQBGUu9F7IgRI3T48GH9+OOPjrY33nhDVqtVERER9R0OAABNHmMzAMBIPGw2m60+P9BisSgmJkadO3fWrFmzlJ+fr9WrV2vo0KEsqA4AQANgbAYAGEm9F7GS9N133+nJJ5/Uxx9/rObNmys6OloLFy7Udde538xaAAA0BYzNAACjaJAiFgAAAACAmqj3Z2IBAAAAAKgpilgAAAAAgGFQxAIAAAAADKPRFrHff/+94uPjNXDgQIWHh+uJJ57Q+fPnXXrv3r17NXr0aJnNZkVHR+vAgQN1HG3DqUmeiouLtW7dOt1111266aabFB4ervj4eB05cqSeoq5/1/LzZPfGG2+od+/eiomJqaMoG9615KmoqEhPPfWURowYoRtuuEGRkZFKSkqq44jrX01zVFJSomeeeUZRUVEaMGCAfvnLX2r9+vWyWq31EHX9O378uJYvX65x48YpNDS0Wv9vmtJ3uNEwNruGsdk1jM2uYWyuGmOza9xpbG52Te92UxaLRVOnTlWnTp2UlJSkc+fOadWqVTp37lyVSwUcPHhQixYt0owZMzRs2DC9+eabevjhh9WyZctGt1ZeTfP0ww8/6M9//rPuvPNOzZkzRxcvXtSOHTt0zz33aPfu3erXr189HkXdu5afJ7vz589r5cqVateuXR1H23CuJU8lJSWaMmWKPDw8tHDhQrVv314nTpzQv/71r3qKvn5cS44ee+wxvfnmm5o3b55CQkL0+eef67nnnpPFYtHvf//7ejqC+nP06FFlZGRowIABqqiokKtzEDal73CjYWx2DWOzaxibXcPYXDXGZte51dhsa4Q2b95sGzBggC0/P9/Rtm/fPluvXr1s33777VXfO3r0aNucOXOc2u6//37bnXfeWSexNqSa5umnn36ylZSUOLVduHDBNmzYMNvixYvrLN6Gci0/T3bPPPOMbcqUKbZFixbZoqOj6yrUBnUteUpMTLSNHDnSVlxcXNdhNqia5qisrMxmNpttSUlJTu1/+MMfbEOHDq2zeBtSeXm54+/V+X/TlL7DjYax2TWMza5hbHYNY3PVGJtd505jc6O8nTgzM1Ph4eEKCAhwtN1+++0ymUzKzMz82fedOHFCOTk5io6OdmqPiYnRF198oXPnztVZzA2hpnlq0aJFpXUDmzdvrp49e+rf//53ncXbUGqaJ7vs7Gylpqbq0UcfrcswG9y15Onll1/WhAkT1LJly7oOs0HVNEc2m03l5eXy8/Nzavf393f5LKjReHpWf3hqat/hRsPY7BrGZtcwNruGsblqjM2uc6exuVEWsdnZ2QoODnZqM5lM6tatm3Jycn72ffZtPXv2dGq37+tq7zWimubpSkpKSvTVV18pKCioNkN0C9eapxUrVmjChAnq1atXXYXoFmqap5MnTyovL09t2rTR7373O5nNZt1000165JFHVFhYWNdh16ua5sjb21vjxo1TamqqPvvsM/300086fPiwXnrpJU2ePLmuwzaMpvYdbjSMza5hbHYNY7NrGJurxthct+rqO7zRPhPr7+9fqd3f3/+q//Hs2/77va1atXLa3ljUNE9X8uyzz+r8+fOaMmVKbYXnNq4lT6+//rq+/fZbrVu3rq7Ccxs1zdPZs2clSWvWrFFkZKQ2b96sU6dOKSEhQfn5+UpJSamzmOvbtfwsrVixQn/4wx909913O9ruu+8+PfDAA7Uep1E1te9wo2Fsdg1js2sYm13D2Fw1xua6VVff4Y2yiEX9eu211/TCCy9o+fLl6t69e0OH4zaKi4u1evVqPfzww1f8csQlFRUVkqTu3bvrmWeekYeHhyTJz89Pc+fO1eeff67+/fs3ZIhuISEhQRkZGXryySfVo0cPffrpp9qwYYPatWun6dOnN3R4ANwMY/OVMTa7hrHZNYzNDadR3k7s7+8vi8VSqd1isTiq/iuxb/vv99rPEFztvUZU0zxd7r333tOSJUsUHx/faG+dqGmeNm3apNatW2vUqFGyWCyyWCwqKytTRUWFLBZLo5t+/Vr/3w0dOtQxSNpfS5dmwmssapqjb7/9Vtu2bdPjjz+uu+66S4MHD9b06dP129/+Vs8995yKi4vrMmzDaGrf4UbD2OwaxmbXMDa7hrG5aozNdauuvsMbZRHbs2dPZWdnO7VZrVbl5uZe9bkQ+7b/vjfbvq/G9kxJTfNk9/nnn+uBBx7QmDFjtHDhwroKs8HVNE85OTn69ttvFRYWpsGDB2vw4MHav3+/srOzNXjwYO3atauuQ69XNc1T165dZTKZfnZ7aWlprcXY0Gqao2PHjkmS+vbt69QeGhoqq9WqM2fO1H6wBtTUvsONhrHZNYzNrmFsdg1jc9UYm+tWXX2HN8oidsSIETp8+LB+/PFHR9sbb7whq9V61bWIunbtqqCgoEqL7+7fv19ms9lp1rLGoKZ5ki794E2fPl2DBg3SypUrnc7SNTY1zdNDDz2kHTt2OP255ZZb1LlzZ+3YsUOjR4+uj/DrTU3zZDKZNGzYML3//vtOs/m99957kqQbbrih7oKuZzXNUefOnSVJR44ccWr/8ssv5eHhoU6dOtVNwAbT1L7DjYax2TWMza5hbHYNY3PVGJvrVp19h9d4cR43VlhYaBs+fLjtnnvusWVmZtpeffVVW1hYmO2hhx5y6rdkyRJb3759ndoOHDhg6927t23t2rW2w4cP25566ilb7969be+88059HkK9qGmezp49a4uIiLANGzbM9v7779s++eQTx58jR47U92HUuWv5efpvjXktumvJ0xdffGHr16+f7aGHHrJlZmbadu/ebRsyZIjt17/+dX0eQp2raY4uXrxomzBhgm3o0KG2F1980fb+++/bNm3aZOvfv7/t97//fX0fRr0oKSmxpaen29LT021TpkyxRUREOF6fPHnSZrPxHW40jM2uYWx2DWOzaxibq8bY7Dp3Gpsb5cRO/v7+euGFF/Tkk0/qwQcfVPPmzRUdHV3ptpqKigqVl5c7tY0ZM0YXLlzQpk2blJKSom7duikhIaHKs59GVNM8HTt2TKdPn5Z0aQa2y3Xu3FmHDh2q89jr07X8PDUl15KnG264Qc8//7wSEhI0a9Ys+fr6auzYsVqwYEF9HkKdq2mOvLy8tGnTJiUlJWnLli06e/asfvGLX+jXv/61fvvb39b3YdSL/Px8zZ0716nN/nrVqlWKi4tr8t/hRsPY7BrGZtcwNruGsblqjM2uc6ex2cNma6Sr8QIAAAAAGp1G+UwsAAAAAKBxoogFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhaAJCkyMlKLFy92vD558qR69+6tPXv2VPnedevWqXfv3nUZHgAATV51xmagMaOIBQAAAGrB+fPntW7dOn344YcNHQrQqDVr6AAAuKfOnTvr888/V7NmfE0AAOCK8+fPa/369XrggQcUFhZW6/tnbAYu4UosgCvy8PBQ8+bN5eXl1dChAADQKJWUlFSrP2MzcAlFLFCP3nvvPfXu3Vt/+9vfKm1766231Lt3b2VkZFx1H2VlZRoyZIgWLlxYaduFCxc0aNAgx7OtVqtVzz33nO68804NHjxY/fv314QJE/Tmm29WGevPPXfzz3/+U3feeafMZrOioqK0e/fuKvcFAIA7q43x+eTJkxo6dKgkaf369erdu7d69+7tGJPt80d8++23WrhwoYYMGaKYmBhJ0qlTp/T4449rzJgxGjBggG666Sb99re/1TfffFPpM/57bLbvNycnR4sXL9ZNN92k//mf/9GSJUt0/vz5a8oL4K64FwGoR0OHDlWHDh20b98+/fKXv3Tatm/fPgUGBuqWW2656j68vb01atQopaenq7S0VM2bN3dsy8jI0E8//aSxY8dKkoqLi/XnP/9ZY8eOVVxcnKxWq1577TXNnj1bW7ZsUURERLXi/+abbxQfH6+AgAA9+OCDKi8v1/r16xUQEFCt/QAA4E5qY3wOCAjQY489pscee0yjRo3SqFGjJEndunVz6jdv3jx16dJFc+fOVVlZmSTpiy++0D//+U/dfvvt6tSpk/79739r9+7duvfee7V//361b9++ymN4+OGH1bVrVz388MP6f//v/yktLU0BAQFXPOkNGB1FLFCPPD099atf/UovvPCCCgsL1apVK0mXis23335bkyZNcukWoejoaL388svKzMx0DJKSdODAAbVp00Y333yzJKlVq1Z6++23ZTKZHH0mT56suLg4bd++vdpF7HPPPaeKigrt3LlTnTp1kiSNHj3acSYZAAAjqo3xuUWLFrr99tv12GOPqXfv3ho3btwV+wUFBWndunVObbfeeqtGjx7t1DZu3DiNHTtWL7/8smbNmlXlMfTt21erVq1yvC4oKNDLL79MEYtGiduJgXo2fvx4Wa1WpaenO9oOHjyo0tLSnx3w/ltYWJjatWunAwcOONpKSkqUkZGhX/7yl44JH7y8vBwFrNVqVUFBgYqLi3XTTTfpyJEj1Yq7vLxc7777riIjIx0FrCRdf/31VZ6dBgDA3dXG+OyKSZMmVWrz8fFx/P38+fP68ccf1bJlS11//fUuj9d333230+ubbrrJMe4DjQ1XYoF61rNnT5nNZu3bt0/33HOPpEu3KoWEhCg0NNSlfXh5een222/Xnj17VFJSohYtWujQoUM6f/68oqOjnfqmpaXpT3/6k7Kzs2Wz2RztHh4e1Yr73LlzunDhgnr06FFp25XaAAAwktoYn13RtWvXSm2lpaVKSkrSvn37lJeX57StdevWLu338hPMkuTv7y9JKiwslK+vb82CBdwUV2KBBnDHHXcoKytLJ0+e1L/+9S/94x//0K9+9atq7WPs2LE6f/683nnnHUmXbiVu3769Bg8e7Oizb98+LVu2TF27dtXq1au1detWbd++XTExMU4FLQAAqJ3xuSqXX3W1e+KJJ7R9+3aNGTNGiYmJSklJ0fbt2xUSEuLyeO3peeVf6xnv0RhxJRZoANHR0Vq9erX27dsnb29vSar2IPk///M/+sUvfqEDBw5oxIgR+vvf/6577rnHaRA7ePCgunbtquTkZKcrr6+88kq1Yw4ICJCPj4++//77Stuu1AYAgNFc6/hc3buc7A4ePKg77rhDS5cudWovLCxUmzZtarRPoDGjiAUaQJs2bXTrrbdq3759MplMCgsLU8eOHau1Dw8PD40ZM0Y7d+7U3r17ZbVaK91KbJ+EwmazOQbWEydOuLTEzn/z8vLSLbfcorfffls//PCD47al7777Tu+++2619wcAgLu51vH5uuuuk3Sp+KwOLy+vSldM9+/fr3//+988sgNcAUUs0EDuuOMOzZ49W5K0evXqGu1j7Nix2rZtm9auXavOnTvrxhtvdNoeGRmpv/3tb5o5c6YiIyN15swZ7dq1S9dff72++uqran/egw8+qL///e+aPHmyJk2apIqKCv3f//2fevbsWWktOwAAjOhaxmcfHx+FhITowIEDuv7669W6dWt16dJFAwYMuOr7IiMjtXfvXvn6+iokJERfffWV0tPTr/j8LACKWKDBREREqE2bNrpw4UKlNelcZTab1b17dx0/flz/+7//W2n7+PHjlZ+frxdffFHvv/++unfvriVLlig3N7dGRWyfPn2UkpKiVatW6bnnnlPHjh31wAMPKC8vjyIWANAoXOv4/NRTT+nJJ5/U6tWrZbVaNX78+CqL2KVLl6pZs2Y6cOCASkpKdMMNN2jr1q16+umna3oYQKPmYeNpb6BBlJeXKyIiQmFhYUpISGjocAAAgBifASNgdmKggbz99tvKy8vT+PHjGzoUAADw/2N8BtwfV2KBevbZZ5/p22+/VXJyslq2bKl9+/Y5Jl2yWq1VTgbRokULtWzZsj5CBQCgyWB8BoyDZ2KBevbiiy9q37596t27t1atWuU0Hf8nn3yiqVOnXvX9DzzwgB588MG6DhMAgCaF8RkwDq7EAm6ksLBQR44cuWqfrl27MlshAAD1iPEZcC8UsQAAuJHjx48rJSVFn332mY4ePaqgoCDt37+/Ur+MjAw9++yzOnbsmDp06KBp06bp3nvvrdQvJSVFO3fu1NmzZxUcHKyFCxdq6NChTn2Ki4u1Zs0a/fWvf5XValVYWJiWLVumLl261NlxAgBQU4a+nfjHH39SRcW11eBt2/oqP7+4liJqvMiTa8iTa8iTa8hT1WorR56eHmrTxj2eZTt69KgyMjI0YMAAVVRU6Ernmj/55BPNmjVL48aN06JFi5SVlaWVK1eqWbNmmjRpkqNfSkqKEhMTNW/ePIWGhiotLU0zZsxQWlqa+vTp4+g3f/58HTlyRI8++qh8fX313HPP6b777tNrr72m6667rlrxMzbXH/LkGvLkGvLkGvJUtfoYmw1dxFZU2K55oLTvB1UjT64hT64hT64hT1VrbDmKjIxUVFSUJGnx4sX68ssvK/XZsGGDQkNDtXLlSklSeHi4Tp8+rQ0bNmjixIny9PSU1WpVcnKypk6dqvj4eEnSkCFDFBsbq+TkZCUlJUm6NJnNO++8oy1btigiIkKS1KtXL40aNUp79uzR5MmTqxU/Y3P9Ik+uIU+uIU+uIU9Vq+scscQOAABuxNPz6kOz1WrV4cOHNXbsWKf2mJgY5eXlOZ7by8rKUlFRkaKjox19vLy8NGbMGGVmZjqu8GZkZMjPz0/Dhw939OvUqZMGDRqkzMzM2josAABqDUUsAAAGkpubq7KyMvXs2dOpPSQkRJKUk5MjScrOzpakSv2Cg4NVUlKiM2fOOPoFBQVVKp6Dg4Md+wIAwJ1QxAIAYCD2tSr9/f2d2u2v7dstFotMJpN8fHyc+rVq1UqSVFBQ4Ojn5+dX6XP8/f2rXBcTAICGYOhnYgEAgHtp29a3VvYTGFi5sEZl5Mk15Mk15Mk15KlqdZ0jilgAAAzEfiXVYrE4tdtf27f7+/vLarWqtLRUzZs3d/SzX11t3bq1o9/p06crfY7FYnHsqzry84uveUKPwEA/5eUVXdM+mgLy5Bry5Bry5BryVLXaypGnp8fPnhjldmIAAAykW7du8vb2rvS86rFjxyRJQUFBkv7zLKz92Vi77OxstWzZUh06dHD0++677yot5XPs2DHHvgAAcCcUsQAAGIjJZFJ4eLjS09Od2vfv36/AwED169dPkjRo0CD5+fnpwIEDjj7l5eVKT0/X8OHD5eHhIUmKiIiQxWLR3//+d0e/06dPKysrSyNGjKiHIwIAoHq4nRgAADdy/vx5ZWRkSJJOnTql4uJiHTx4UJJkNpvVuXNnzZ49W1OmTNGyZcsUGxurrKwspaWlafny5Y5Zhk0mk2bOnKnExEQFBAQoNDRUaWlpys3NVUJCguPzBgwYoFtvvVVLly7V4sWL5evrq6SkJP3iF79QXFxc/ScAAIAqUMQCAOBG8vPzNXfuXKc2++tVq1YpLi5OAwcO1MaNG7V27Vrt3btX7du315IlSzRp0iSn98XHx0uSUlNTdfbsWYWEhGjLli3q06ePU7+EhAStWbNGjz/+uKxWq8LCwpSUlKTrrruuDo8UAICa8bD990MwBlIbk0e0at1CJm+vWoqodlwovagiy/mGDsMJD7G7hjy5hjy5hjxVrT4mj0D1MDbXH74jXEOeXEOeXEOeqlYfY3OTvxJr8vZS7Py/NHQYTl5LGCf+awAAmirGZgDA1TCxEwAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADCMKovY9PR0zZo1SxEREbrxxhsVGxurXbt2qaKiwqlfRkaGxo8fL7PZrKioKKWmpl5xfykpKYqMjFT//v0VFxenDz74oHaOBAAAAADQ6FVZxG7fvl0mk0mPPPKINm3apKioKD311FN6+umnHX0++eQTzZo1S3379tXWrVsVFxenlStX6sUXX3TaV0pKihITEzV58mRt3rxZPXr00IwZM/T111/X/pEBAAAAABqdZlV12LRpkwICAhyvw8PDVVJSop07d2revHkymUzasGGDQkNDtXLlSkef06dPa8OGDZo4caI8PT1ltVqVnJysqVOnKj4+XpI0ZMgQxcbGKjk5WUlJSXV0iAAAAACAxqLKK7GXF7B2ffv2VWlpqQoKCmS1WnX48GGNHTvWqU9MTIzy8vJ05MgRSVJWVpaKiooUHR3t6OPl5aUxY8YoMzNTNpvtWo8FAAAAANDI1Whip48//litW7dW27ZtlZubq7KyMvXs2dOpT0hIiCQpJydHkpSdnS1JlfoFBwerpKREZ86cqUkoAAAAAIAmpMrbif/bF198oT179mj27Nny8vJSYWGhJMnf39+pn/21fbvFYpHJZJKPj49Tv1atWkmSCgoK1LFjx2rF0ratb3XDN4zAQL+GDqESd4zJHZEn15An15CnqpEjAACalmoVsXl5eZozZ47MZrOmT59eVzG5LD+/WBUV13Ybsrv+8pOXV9TQITgJDPRzu5jcEXlyDXlyDXmqWm3lyNPTo1GfGAUAoDFx+XbioqIiTZ8+XT4+PkpOTpa3t7ek/1xJtVgsTv3tr+3b/f39ZbVaVVpa6tTPfqW2devWNTsCAAAAAECT4VIRW1paqpkzZyo/P1/PP/+82rRp49jWrVs3eXt7O559tTt27JgkKSgoSNJ/noW1Pxtrl52drZYtW6pDhw41PwoAAJqYN998UxMmTNDAgQM1bNgwPfjgg/r+++8r9du7d69Gjx4ts9ms6OhoHThwoFKfsrIyJSQk6JZbbtGAAQM0ZcoUffXVV/VwFAAAVF+VRezFixc1d+5cffPNN9q6das6d+7stN1kMik8PFzp6elO7fv371dgYKD69esnSRo0aJD8/PycBs/y8nKlp6dr+PDh8vDwqI3jAQCg0fvggw/0wAMPKCgoSOvXr9eyZcuUk5Oj+++/X8XFxY5+Bw8e1KJFizRq1Cht3bpVQ4cO1cMPP6yMjAyn/a1atUo7d+7UnDlztHHjRnl7e+u+++5j0kUAgFuq8pnYFStW6O2339bChQt14cIFffrpp45twcHB8vX11ezZszVlyhQtW7ZMsbGxysrKUlpampYvXy5Pz0t1sslk0syZM5WYmKiAgACFhoYqLS1Nubm5SkhIqLMDBACgsdm/f786deqkP/7xj46TwJ07d9Zdd92ljz/+WBEREZKkpKQkjR49WvPnz5d0aR33nJwcrVu3ztHnzJkz2r17t5YuXaq7775bkjRgwADddttteuGFF/TII480wBECAPDzqixi3333XUnS008/XWnbjh07FBYWpoEDB2rjxo1au3at9u7dq/bt22vJkiWaNGmSU//4+HhJUmpqqs6ePauQkBBt2bJFffr0qY1jAQCgSbh48aJatmzpdBeTn5/zRIUnTpxQTk6O5s2b59QeExOjJUuW6Ny5cwoICNC7776r8vJyp/XefX19NXLkSGVmZlLEAgDcTpVF7KFDh1zaUUREhOOs7tXEx8c7ilkAAFB948eP1/79+5Wamqpx48bJYrHoj3/8o3r27KmhQ4dK+s867Vdan92+PSAgQNnZ2WrXrp3TfBf2fvv371dFRYXjrioAANxBtdeJBQAADSs8PFzr1q3TggUL9OSTT0qSevXqpe3bt8tkMknSz67jbl814PJ13P/7Kq69X1lZmUpKSuTr6/ryQ415qSJ3XJbPHWNyR+TJNeTJNeSpanWdI4pYAAAMJisrS4sWLdKECRMUGRmpgoICbdy4UTNnztSuXbvk4+PTYLGxhnv9YS1p15An15An15CnqtXHGu4UsQAAGMyTTz6psLAw/f73v3e03Xjjjbr11lv1l7/8RRMnTnRaxz0wMNDRz34F9vJ13IuKKv+yUVhYKG9vb7Vo0aIuDwUAgGrjIRcAAAwmOzu70qSIHTt2VJs2bZSbmyvpP+u0//c67vb12i9fxz0/P18FBQWV+vXo0YPnYQEAboeRCQAAg+nUqZOOHDni1Hbq1Cn9+OOPjvXcu3btqqCgIKf12aVLy/OYzWYFBARIkm655RZ5eno6rff+008/6dChQxoxYkQdHwkAANXH7cQAABjM5MmT9cQTT+iJJ57QbbfdpoKCAiUnJ6tt27YaM2aMo9+cOXM0b948devWTTfffLPeeustvffee9q8ebOjT4cOHXTPPffomWeeUbNmzdSpUydt27ZNkjRt2rR6PzYAAKpCEQsAgMFMnjxZ3t7e2rVrl/bs2aOWLVtqwIABevbZZ52WyhkzZowuXLigTZs2KSUlRd26dVNCQkKlJfGWLFmiFi1a6Nlnn1VRUZHMZrO2b9+uDh061PehAQBQJYpYAAAMxsPDQxMnTtTEiROr7Dt+/HiNHz/+qn28vb21YMECLViwoLZCBACgzvBMLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYTRr6AAAAMbg53+dfJq717BhLStv6BAAAEA9c6/fRgAAbsuneTPFzv9LQ4fh5LWEcQ0dAgAAqGfcTgwAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMFwqYo8fP67ly5dr3LhxCg0NVUxMTKU+ixcvVu/evSv9OXjwYKW+KSkpioyMVP/+/RUXF6cPPvjg2o8EAAAAANDoNXOl09GjR5WRkaEBAwaooqJCNpvtiv26du2qZ555xqmtR48eTq9TUlKUmJioefPmKTQ0VGlpaZoxY4bS0tLUp0+fmh0FAAAAAKBJcKmIjYyMVFRUlKRLV1y//PLLK/bz8fHRjTfe+LP7sVqtSk5O1tSpUxUfHy9JGjJkiGJjY5WcnKykpKRqhg8AAAAAaEpcup3Y07N2Hp3NyspSUVGRoqOjHW1eXl4aM2aMMjMzf/YKLwAAAAAAUi1P7JSbm6ubbrpJ/fr10x133KEDBw44bc/OzpYk9ezZ06k9ODhYJSUlOnPmTG2GAwAAAABoZFy6ndgVffv2ldlsVnBwsIqKivTyyy9r3rx5unDhguLi4iRJFotFJpNJPj4+Tu9t1aqVJKmgoEAdO3Z0+TPbtvWtrfDdTmCgX0OHUIk7xuSOyJNryJNryFPVyBEAAE1LrRWx06ZNc3odFRWlqVOnat26dY4itrbl5xerouLabkF2119+8vKKGjoEJ4GBfm4XkzsiT64hT65xtzw15u9LT08PQ54Y3bt3r3bs2KFjx47puuuuU2hoqBISEhQQECBJysjI0LPPPqtjx46pQ4cOmjZtmu69995K+0lJSdHOnTt19uxZBQcHa+HChRo6dGh9Hw4AAC6ptSL2SkaPHq3HH39c586dU0BAgPz9/WW1WlVaWqrmzZs7+hUWFkqSWrduXZfhAADQaCQnJ2vLli2aMWOGFi1apKKiIn344YcqKyuTJH3yySeaNWuWxo0bp0WLFikrK0srV65Us2bNNGnSJMd+WDUAAIzLz/86+TSv05Ku2qxl5XX+GfV6xPZnYbOzsxUaGupoz87OVsuWLdWhQ4f6DAcAAEPKycnR+vXrtX79eo0cOdLRbl9JQJI2bNig0NBQrVy5UpIUHh6u06dPa8OGDZo4caI8PT1ZNQAADM6neTPFzv9LQ4fh5LWEcXX+GbU6sdPlbDab0tPT1blzZ8dtTYMGDZKfn5/ThE/l5eVKT0/X8OHD5eHhUVfhAADQaOzZs0edOnVyKmAvZ7VadfjwYY0dO9apPSYmRnl5eTpy5IgkVg0AABiTS1diz58/r4yMDEnSqVOnVFxcrIMHD0qSzGazpEvrx0ZHR6t79+6yWCxKS0vTRx99pDVr1jj2YzKZNHPmTCUmJiogIMBx21Jubq4SEhJq+9gAAGiUPvvsM/Xu3VsbN27Uzp07VVBQoL59++qRRx7RkCFDlJubq7KyskqrAYSEhEi6dCXXbDa7tGpAdSZcBACgPrhUxObn52vu3LlObfbXq1atUmRkpHx9fZWcnKz8/Hx5e3srNDRUycnJioyMdHqf/Xal1NRUnT17ViEhIdqyZQvP3QAA4KK8vDx9+eWX+vrrr7V06VL5+vpq27Zt+s1vfqMDBw445prw9/d3ep/9tX17ba8aILFyQH1zx5jcEXlyDXlyDXmqWl3nyKUitkuXLvrmm2+u2ic5OdnlD42Pj3cUswAAoHpsNptKSkq0a9cu9e3bV5I0ePBg3XbbbUpJSVFMTEyDxcbKAfXH3WYwd1fkyTXkyTXulqfG/H15tZUD6uyZWAAAUDf8/f3VunVrRwErSdddd50GDBigo0ePOq6kWiwWp/fZX9u3X75qwOVYNQAA4M4oYgEAMJjg4OCf3VZaWqpu3brJ29tbOTk5TtuOHTsmSQoKCpLkvGrA5Vg1AADgzihiAQAwmJEjR6qgoMAxy7AklZSU6NNPP1W/fv1kMpkUHh6u9PR0p/ft379fgYGB6tevnyRWDQAAGJN7rYwLAACqFBUVpf79+2vOnDmaN2+eWrZsqW3btunChQu6//77JUmzZ8/WlClTtGzZMsXGxiorK0tpaWlavny5PD0vncNm1QAAgBFRxAIAYDCenp7avHmz1qxZo8cff1ylpaUaMGCAduzYoe7du0uSBg4cqI0bN2rt2rXau3ev2rdvryVLlmjSpElO+2LVAACA0VDEAgBgQAEBAVq9evVV+0RERCgiIqLKfbFqAADASHgmFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhuFTEHj9+XMuXL9e4ceMUGhqqmJiYK/bLyMjQ+PHjZTabFRUVpdTU1Cv2S0lJUWRkpPr376+4uDh98MEHNT8CAAAAAECT4VIRe/ToUWVkZKh79+7q2bPnFft88sknmjVrlvr27autW7cqLi5OK1eu1IsvvujULyUlRYmJiZo8ebI2b96sHj16aMaMGfr666+v/WgAAAAAAI1aM1c6RUZGKioqSpK0ePFiffnll5X6bNiwQaGhoVq5cqUkKTw8XKdPn9aGDRs0ceJEeXp6ymq1Kjk5WVOnTlV8fLwkaciQIYqNjVVycrKSkpJq67gAAAAAAI2QS1diPT2v3s1qterw4cMaO3asU3tMTIzy8vJ05MgRSVJWVpaKiooUHR3t6OPl5aUxY8YoMzNTNputuvEDAAAAAJqQWpnYKTc3V2VlZZVuNQ4JCZEk5eTkSJKys7MlqVK/4OBglZSU6MyZM7URDgAATcpPP/2kESNGqHfv3vriiy+ctu3du1ejR4+W2WxWdHS0Dhw4UOn9ZWVlSkhI0C233KIBAwZoypQp+uqrr+orfAAAqqVWitjCwkJJkr+/v1O7/bV9u8Vikclkko+Pj1O/Vq1aSZIKCgpqIxwAAJqU9evXq7y8vFL7wYMHtWjRIo0aNUpbt27V0KFD9fDDDysjI8Op36pVq7Rz507NmTNHGzdulLe3t+677z5OLgMA3JJLz8S6q7ZtfRs6hDoTGOjX0CFU4o4xuSPy5Bry5BryVLWmnqNvv/1Wu3fv1uLFi7V8+XKnbUlJSRo9erTmz58v6dJ8FTk5OVq3bp0iIiIkSWfOnNHu3bu1dOlS3X333ZKkAQMG6LbbbtMLL7ygRx55pH4PCACAKtRKEWu/kmqxWJza7a/t2/39/WW1WlVaWqrmzZs7+tmv1LZu3bpan5ufX6yKimt7jtZdf/nJyytq6BCcBAb6uV1M7og8uYY8ucbd8tSYvy89PT0Me2J0xYoVmjx5snr06OHUfuLECeXk5GjevHlO7TExMVqyZInOnTungIAAvfvuuyovL3ea18LX11cjR45UZmYmRSwAwO3Uyu3E3bp1k7e3t+PZV7tjx45JkoKCgiT951lY+7OxdtnZ2WrZsqU6dOhQG+EAANAk7N27V8ePH9fMmTMrbbOPyVeah+Ly7dnZ2WrXrp3atGlTqd/333+vioqKuggdAIAaq5Ui1mQyKTw8XOnp6U7t+/fvV2BgoPr16ydJGjRokPz8/JwmlSgvL1d6erqGDx8uDw+P2ggHAIBGr6ioSE8//bQWLlyoli1bVtr+c/NV2O+Ouny+Cj+/ylfZW7VqpbKyMpWUlNR26AAAXBOXbic+f/68YxKIU6dOqbi4WAcPHpQkmc1mde7cWbNnz9aUKVO0bNkyxcbGKisrS2lpaVq+fLljiR6TyaSZM2cqMTFRAQEBCg0NVVpamnJzc5WQkFBHhwgAQOPz7LPPqnv37vrVr37V0KE4Mept2a5wx1vq3TEmd0SeXEOeXEOeqlbXOXKpiM3Pz9fcuXOd2uyvV61apbi4OA0cOFAbN27U2rVrtXfvXrVv315LlizRpEmTnN4XHx8vSUpNTdXZs2cVEhKiLVu2qE+fPrVxPAAANHpHjx7V7t27tW3bNsf8E/YrpiUlJSouLnaaryIwMNDxXvsV2MvnqygqqvxccWFhoby9vdWiRYtqxcZ8FfXH3Z6bd1fkyTXkyTXulqfG/H15tfkqXCpiu3Tpom+++abKfhEREY7ZDq8mPj7eUcwCAIDqOX78uC5evKipU6dW2jZ16lT16dNH69evl3Tp2dfLn4u1z0tx+XwV+fn5KigocJpgMTs7Wz169HDcTQUAgLsw9BI7AAA0RYMGDdKOHTuc2r766iutWrVKjz/+uPr166euXbsqKChIBw4c0KhRoxz99u/fL7PZrICAAEnSLbfcIk9PT6Wnpzvunvrpp5906NAh3XnnnfV3UAAAuIgiFgAAgwkICFBYWNgVt/Xr109ms1mSNGfOHM2bN0/dunXTzTffrLfeekvvvfeeNm/e7OjfoUMH3XPPPXrmmWfUrFkzderUSdu2bZMkTZs2re4PBgCAaqKIBQCgkRozZowuXLigTZs2KSUlRd26dVNCQkKlR3+WLFmiFi1a6Nlnn1VRUZHMZrO2b9/O0ncAALdEEQsAQCMQFhZ2xfkrxo8fr/Hjx1/1vd7e3lqwYIEWLFhQV+EBAFBrmK0BAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDqLUids+ePerdu3elPytWrHDql5GRofHjx8tsNisqKkqpqam1FQIAAAAAoJFrVts7fP755+Xn5+d43a5dO8ffP/nkE82aNUvjxo3TokWLlJWVpZUrV6pZs2aaNGlSbYcCAECjlJ6ertdee01HjhxRYWGhunbtqkmTJumee+6Rp+d/zk9nZGTo2Wef1bFjx9ShQwdNmzZN9957b6X9paSkaOfOnTp79qyCg4O1cOFCDR06tD4PCQAAl9V6EduvXz8FBARccduGDRsUGhqqlStXSpLCw8N1+vRpbdiwQRMnTnQaeAEAwJVt375dnTp10iOPPKK2bdvqww8/1FNPPaUTJ05o0aJFklw/cZySkqLExETNmzdPoaGhSktL04wZM5SWlqY+ffo01CECAPCzar2I/TlWq1WHDx/W/PnzndpjYmL00ksv6ciRIzKbzfUVDgAAhrVp0yanE8bh4eEqKSnRzp07NW/ePJlMJpdOHFutViUnJ2vq1KmKj4+XJA0ZMkSxsbFKTk5WUlJSgxwfAABXU+uXPmNjY9W3b19FRkZq/fr1unjxoiQpNzdXZWVl6tmzp1P/kJAQSVJOTk5thwIAQKN0pTue+vbtq9LSUhUUFDhOHI8dO9apT0xMjPLy8nTkyBFJUlZWloqKihQdHe3o4+XlpTFjxigzM1M2m61uDwQAgBqotSuxgYGBevDBB9W/f395eXkpMzNTGzdu1MmTJ7V69WoVFhZKkvz9/Z3eZ39t314dbdv6Xnvgbiow0K/qTvXMHWNyR+TJNeTJNeSpauToko8//litW7dW27Zt9d1331V54thsNis7O1uSKvULDg5WSUmJzpw5o44dO9bPAQAA4KJaK2KHDx+u4cOHO14PGzZMfn5+WrdunWbNmlVbH+MkP79YFRXXdpbYXX/5ycsraugQnAQG+rldTO6IPLmGPLnG3fLUmL8vPT09DH1i9IsvvtCePXs0e/ZseXl5uXzi2GKxyGQyycfHx6lfq1atJEkFBQUUsQAAt1Onz8SOGTNG69at05EjRxxnfy0Wi1Mf+2v7gAkAAFyXl5enOXPmyGw2a/r06Q0djqFPBlTFHU/kuGNM7og8uYY8uYY8Va2uc1RvEzt169ZN3t7eysnJ0YgRIxztx44dkyQFBQXVVygAADQKRUVFmj59unx8fJScnCxvb29J/zkxXNWJY39/f1mtVpWWlqp58+aOfvYrta1bt652TNwlVX/c7W4Nd0WeXEOeXONueWrM35dXu0uqTte0ef311+Xh4aEbbrhBJpNJ4eHhSk9Pd+qzf/9+BQYGql+/fnUZCgAAjUppaalmzpyp/Px8Pf/882rTpo1j2+Unji/33yeO7c/C2p+NtcvOzlbLli3VoUOHujwEAABqpNauxMbHxyssLEy9evWSh4eH/v73v2vXrl2aMGGCunbtKkmaPXu2pkyZomXLlik2NlZZWVlKS0vT8uXLWSMWAAAXXbx4UXPnztU333yj1NRUde7c2Wn75SeO77vvPkf7f584HjRokPz8/HTgwAGFhoZKksrLy5Wenq7hw4fLw8Oj3o4JAABX1VoRGxQUpFdeeUVnzpzRxYsX1aNHDy1YsEDTpk1z9Bk4cKA2btyotWvXau/evWrfvr2WLFnitOg6AAC4uhUrVujtt9/WwoULdeHCBX366aeObcHBwfL19XXpxLHJZNLMmTOVmJiogIAAhYaGKi0tTbm5uUpISGigowMA4OpqrYhdunSpli5dWmW/iIgIRURE1NbHAgDQ5Lz77ruSpKeffrrSth07digsLMzlE8fx8fGSpNTUVJ09e1YhISHasmWL+vTpU/cHAgBADdTbxE4AAKB2HDp0yKV+rp44jo+PdxSzAAC4Ox5EBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADAMilgAAAAAgGFQxAIAAAAADIMiFgAAAABgGBSxAAAAAADDoIgFAAAAABgGRSwAAAAAwDAoYgEAAAAAhkERCwAAAAAwDIpYAAAAAIBhUMQCAAAAAAyDIhYAAAAAYBgUsQAAAAAAw6CIBQAAAAAYBkUsAAAAAMAwKGIBAAAAAIZBEQsAAAAAMAyKWAAAAACAYVDEAgAAAAAMgyIWAAAAAGAYFLEAAAAAAMOgiAUAAAAAGAZFLAAAAADAMChiAQAAAACGQRELAAAAADCMBiliv//+e8XHx2vgwIEKDw/XE088ofPnzzdEKAAAQIzNAADjaFbfH2ixWDR16lR16tRJSUlJOnfunFatWqVz584pMTGxvsMBAKDJY2wGABhJvRexu3fvlsVi0d69exUQECBJ8vLy0oIFCzRr1iyFhITUd0gAADRpjM0AACOp99uJMzMzFR4e7hgkJen222+XyWRSZmZmfYcDAECTx9gMADCSer8Sm52drTvvvNOpzWQyqVu3bsrJyanWvjw9PWolpvZtrquV/dSm2jq22uSOMbkj8uQa8uQad8tTY/2+dLc81zfGZte448+JO8bkjsiTa8iTa9wtT431+/Jq+2iQZ2L9/f0rtfv7+6uwsLBa+2rTpmWtxJSy7Je1sp/a1Latb0OHUIk7xuSOyJNryJNr3C1PfF82TozNrnHHnzV3jMkdkSfXkCfXuFuemuL3JUvsAAAAAAAMo96LWH9/f1kslkrtFotFrVq1qu9wAABo8hibAQBGUu9FbM+ePZWdne3UZrValZubq6CgoPoOBwCAJo+xGQBgJPVexI4YMUKHDx/Wjz/+6Gh74403ZLVaFRERUd/hAADQ5DE2AwCMxMNms9nq8wMtFotiYmLUuXNnzZo1S/n5+Vq9erWGDh3KguoAADQAxmYAgJHUexErSd99952efPJJffzxx2revLmio6O1cOFCXXed+00PDQBAU8DYDAAwigYpYgEAAAAAqAmW2AEAAAAAGAZFLAAAAADAMBptEfv9998rPj5eAwcOVHh4uJ544gmdP3/epffu3btXo0ePltlsVnR0tA4cOFDH0TacmuSpuLhY69at01133aWbbrpJ4eHhio+P15EjR+op6vp3LT9Pdm+88YZ69+6tmJiYOoqy4V1LnoqKivTUU09pxIgRuuGGGxQZGamkpKQ6jrj+1TRHJSUleuaZZxQVFaUBAwbol7/8pdavXy+r1VoPUde/48ePa/ny5Ro3bpxCQ0Or9f+mKX2HGw1js2sYm13D2OwaxuaqMTa7xp3G5mbX9G43ZbFYNHXqVHXq1ElJSUk6d+6cVq1apXPnzlU5y+LBgwe1aNEizZgxQ8OGDdObb76phx9+WC1btmx0ywzUNE8//PCD/vznP+vOO+/UnDlzdPHiRe3YsUP33HOPdu/erX79+tXjUdS9a/l5sjt//rxWrlypdu3a1XG0Deda8lRSUqIpU6bIw8NDCxcuVPv27XXixAn961//qqfo68e15Oixxx7Tm2++qXnz5ikkJESff/65nnvuOVksFv3+97+vpyOoP0ePHlVGRoYGDBigiooKuTp9Q1P6DjcaxmbXMDa7hrHZNYzNVWNsdp1bjc22Rmjz5s22AQMG2PLz8x1t+/bts/Xq1cv27bffXvW9o0ePts2ZM8ep7f7777fdeeeddRJrQ6ppnn766SdbSUmJU9uFCxdsw4YNsy1evLjO4m0o1/LzZPfMM8/YpkyZYlu0aJEtOjq6rkJtUNeSp8TERNvIkSNtxcXFdR1mg6ppjsrKymxms9mWlJTk1P6HP/zBNnTo0DqLtyGVl5c7/l6d/zdN6TvcaBibXcPY7BrGZtcwNleNsdl17jQ2N8rbiTMzMxUeHq6AgABH2+233y6TyaTMzMyffd+JEyeUk5Oj6Ohop/aYmBh98cUXOnfuXJ3F3BBqmqcWLVpUWnKhefPm6tmzp/7973/XWbwNpaZ5ssvOzlZqaqoeffTRugyzwV1Lnl5++WVNmDBBLVu2rOswG1RNc2Sz2VReXi4/Pz+ndn9/f5fPghqNp2f1h6em9h1uNIzNrmFsdg1js2sYm6vG2Ow6dxqbG2URm52dreDgYKc2k8mkbt26KScn52ffZ9/Ws2dPp3b7vq72XiOqaZ6upKSkRF999ZWCgoJqM0S3cK15WrFihSZMmKBevXrVVYhuoaZ5OnnypPLy8tSmTRv97ne/k9ls1k033aRHHnlEhYWFdR12vappjry9vTVu3Dilpqbqs88+008//aTDhw/rpZde0uTJk+s6bMNoat/hRsPY7BrGZtcwNruGsblqjM11q66+wxvtM7H+/v6V2v39/a/6H8++7b/f26pVK6ftjUVN83Qlzz77rM6fP68pU6bUVnhu41ry9Prrr+vbb7/VunXr6io8t1HTPJ09e1aStGbNGkVGRmrz5s06deqUEhISlJ+fr5SUlDqLub5dy8/SihUr9Ic//EF33323o+2+++7TAw88UOtxGlVT+w43GsZm1zA2u4ax2TWMzVVjbK5bdfUd3iiLWNSv1157TS+88IKWL1+u7t27N3Q4bqO4uFirV6/Www8/fMUvR1xSUVEhSerevbueeeYZeXh4SJL8/Pw0d+5cff755+rfv39DhugWEhISlJGRoSeffFI9evTQp59+qg0bNqhdu3aaPn16Q4cHwM0wNl8ZY7NrGJtdw9jccBrl7cT+/v6yWCyV2i0Wi6PqvxL7tv9+r/0MwdXea0Q1zdPl3nvvPS1ZskTx8fGN9taJmuZp06ZNat26tUaNGiWLxSKLxaKysjJVVFTIYrE0uunXr/X/3dChQx2DpP21dGkmvMaipjn69ttvtW3bNj3++OO66667NHjwYE2fPl2//e1v9dxzz6m4uLguwzaMpvYdbjSMza5hbHYNY7NrGJurxthct+rqO7xRFrE9e/ZUdna2U5vValVubu5Vnwuxb/vve7Pt+2psz5TUNE92n3/+uR544AGNGTNGCxcurKswG1xN85STk6Nvv/1WYWFhGjx4sAYPHqz9+/crOztbgwcP1q5du+o69HpV0zx17dpVJpPpZ7eXlpbWWowNraY5OnbsmCSpb9++Tu2hoaGyWq06c+ZM7QdrQE3tO9xoGJtdw9jsGsZm1zA2V42xuW7V1Xd4oyxiR4wYocOHD+vHH390tL3xxhuyWq1XXYuoa9euCgoKqrT47v79+2U2m51mLWsMapon6dIP3vTp0zVo0CCtXLnS6SxdY1PTPD300EPasWOH059bbrlFnTt31o4dOzR69Oj6CL/e1DRPJpNJw4YN0/vvv+80m997770nSbrhhhvqLuh6VtMcde7cWZJ05MgRp/Yvv/xSHh4e6tSpU90EbDBN7TvcaBibXcPY7BrGZtcwNleNsblu1dl3eI0X53FjhYWFtuHDh9vuueceW2Zmpu3VV1+1hYWF2R566CGnfkuWLLH17dvXqe3AgQO23r1729auXWs7fPiw7amnnrL17t3b9s4779TnIdSLmubp/2vvfl1Vh8M4jj8Xg0XsIvgPKEZBDMtqE6NpRRBEg8ksmAy2IRpM+h+sGQyrBrEZBcusYlCfGy73cM69waE4znfn/YKFLe15+LIPz9gP3/fVsiwtlUrqeZ5uNpuPbbfbhV3G272ynv4V5X/RvdKn7Xar2WxWu92urtdrXS6XWigU1LbtMEt4u2d7dL1etV6va7FY1MVioZ7nqeM4ms/ntd/vh11GKM7ns7quq67raqPRUMuyPvYPh4Oqcg03DdkcDNkcDNkcDNn8GNkc3HfK5kh+2CmZTMp8PpfBYCDtdlvi8bhUq9X/Hqu53+9yu92+HCuXy3K5XMRxHJnNZpLJZGQ0Gj28+2miZ/u03+/leDyKyJ8vsH2WTqdltVq9/dzD9Mp6+kle6VMul5PpdCqj0UharZYkEgmpVCrS6/XCLOHtnu1RLBYTx3FkPB7LZDIR3/cllUqJbdvSbDbDLiMUp9NJOp3Ol2N/94fDodRqtR9/DTcN2RwM2RwM2RwM2fwY2Rzcd8rmX6oR/RsvAAAAACByIvlOLAAAAAAgmhhiAQAAAADGYIgFAAAAABiDIRYAAAAAYAyGWAAAAACAMRhiAQAAAADGYIgFAAAAABiDIRYAAAAAYAyGWAAAAACAMX4DO8DyLHAiLR0AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x720 with 4 Axes>"
]
@@ -1804,7 +1801,7 @@
},
{
"cell_type": "code",
- "execution_count": 319,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": []
@@ -1826,7 +1823,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -1840,7 +1837,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.3"
+ "version": "3.10.4"
}
},
"nbformat": 4,
diff --git a/ass01/Analysis of Mystery Machine.ipynb b/ass01/Analysis of Mystery Machine.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 70,
+ "execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
@@ -15,8 +15,8 @@
"\n",
"from scipy.optimize import curve_fit\n",
"\n",
- "import sklearn.neighbors as neighbors\n",
- "from sklearn.model_selection import train_test_split"
+ "from sklearn.model_selection import train_test_split\n",
+ "from sklearn.tree import DecisionTreeClassifier "
]
},
{
@@ -33,7 +33,7 @@
},
{
"cell_type": "code",
- "execution_count": 71,
+ "execution_count": 30,
"metadata": {
"scrolled": true
},
@@ -254,7 +254,7 @@
"[5 rows x 100 columns]"
]
},
- "execution_count": 71,
+ "execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
@@ -281,7 +281,7 @@
},
{
"cell_type": "code",
- "execution_count": 72,
+ "execution_count": 31,
"metadata": {},
"outputs": [
{
@@ -600,7 +600,7 @@
"[8 rows x 100 columns]"
]
},
- "execution_count": 72,
+ "execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
@@ -618,7 +618,7 @@
},
{
"cell_type": "code",
- "execution_count": 73,
+ "execution_count": 32,
"metadata": {},
"outputs": [
{
@@ -655,7 +655,7 @@
},
{
"cell_type": "code",
- "execution_count": 74,
+ "execution_count": 33,
"metadata": {},
"outputs": [
{
@@ -664,7 +664,7 @@
"Text(0.5, 1.0, 'Distribution of min value--- not running')"
]
},
- "execution_count": 74,
+ "execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
@@ -756,7 +756,7 @@
},
{
"cell_type": "code",
- "execution_count": 75,
+ "execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
@@ -779,7 +779,7 @@
},
{
"cell_type": "code",
- "execution_count": 76,
+ "execution_count": 35,
"metadata": {},
"outputs": [
{
@@ -788,7 +788,7 @@
"Text(0.5, 1.0, 'Distribution of min value--- not running')"
]
},
- "execution_count": 76,
+ "execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
@@ -846,7 +846,7 @@
},
{
"cell_type": "code",
- "execution_count": 77,
+ "execution_count": 36,
"metadata": {},
"outputs": [
{
@@ -1271,7 +1271,7 @@
"[100 rows x 100 columns]"
]
},
- "execution_count": 77,
+ "execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
@@ -1282,7 +1282,7 @@
},
{
"cell_type": "code",
- "execution_count": 78,
+ "execution_count": 37,
"metadata": {
"scrolled": false
},
@@ -1329,7 +1329,7 @@
},
{
"cell_type": "code",
- "execution_count": 79,
+ "execution_count": 38,
"metadata": {},
"outputs": [
{
@@ -1338,7 +1338,7 @@
"Text(0.5, 1.0, 'Blue Switch On')"
]
},
- "execution_count": 79,
+ "execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
@@ -1367,7 +1367,7 @@
},
{
"cell_type": "code",
- "execution_count": 104,
+ "execution_count": 39,
"metadata": {},
"outputs": [
{
@@ -1376,7 +1376,7 @@
"[Text(0.5, 0, 'Blue Switch On'), Text(1.5, 0, 'Blue Switch Off')]"
]
},
- "execution_count": 104,
+ "execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
@@ -1421,7 +1421,7 @@
},
{
"cell_type": "code",
- "execution_count": 81,
+ "execution_count": 40,
"metadata": {},
"outputs": [
{
@@ -1453,7 +1453,7 @@
},
{
"cell_type": "code",
- "execution_count": 82,
+ "execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
@@ -1474,7 +1474,7 @@
},
{
"cell_type": "code",
- "execution_count": 83,
+ "execution_count": 42,
"metadata": {},
"outputs": [
{
@@ -1510,7 +1510,7 @@
},
{
"cell_type": "code",
- "execution_count": 84,
+ "execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
@@ -1541,7 +1541,7 @@
},
{
"cell_type": "code",
- "execution_count": 132,
+ "execution_count": 44,
"metadata": {},
"outputs": [],
"source": [
@@ -1559,16 +1559,16 @@
},
{
"cell_type": "code",
- "execution_count": 133,
+ "execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "0.8668341708542714"
+ "0.8567839195979899"
]
},
- "execution_count": 133,
+ "execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
@@ -1600,7 +1600,7 @@
},
{
"cell_type": "code",
- "execution_count": 87,
+ "execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
@@ -1624,16 +1624,16 @@
},
{
"cell_type": "code",
- "execution_count": 88,
+ "execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "<matplotlib.collections.PathCollection at 0x7fe61badfa60>"
+ "<matplotlib.collections.PathCollection at 0x7f5b4054b010>"
]
},
- "execution_count": 88,
+ "execution_count": 47,
"metadata": {},
"output_type": "execute_result"
},
@@ -1662,7 +1662,7 @@
},
{
"cell_type": "code",
- "execution_count": 296,
+ "execution_count": 48,
"metadata": {},
"outputs": [
{
@@ -1672,15 +1672,12 @@
" min_samples_split=7, random_state=100)"
]
},
- "execution_count": 296,
+ "execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "from sklearn.ensemble import RandomForestClassifier\n",
- "from sklearn.tree import DecisionTreeClassifier \n",
- "from sklearn.model_selection import GridSearchCV\n",
"\n",
"dum2_train = data_train[data_train[:,1]==1]\n",
"d2_train = dum2_train[dum2_train[:,82] <= 3.5]\n",
@@ -1697,7 +1694,7 @@
},
{
"cell_type": "code",
- "execution_count": 297,
+ "execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
@@ -1725,7 +1722,7 @@
},
{
"cell_type": "code",
- "execution_count": 299,
+ "execution_count": 50,
"metadata": {},
"outputs": [
{
@@ -1755,18 +1752,18 @@
},
{
"cell_type": "code",
- "execution_count": 322,
+ "execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"X_test = np.array(data_test)[:,1:]\n",
"pred3 = predict(X_test, clf)\n",
- "np.savetxt('./prediction.txt', pred3, fmt='%1g')"
+ "np.savetxt('./prediction.csv', pred3, fmt='%1g', delimiter=',')"
]
},
{
"cell_type": "code",
- "execution_count": 321,
+ "execution_count": 54,
"metadata": {},
"outputs": [
{
@@ -1775,13 +1772,13 @@
"Text(0.5, 1.0, 'y_train')"
]
},
- "execution_count": 321,
+ "execution_count": 54,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1152x720 with 4 Axes>"
]
@@ -1804,7 +1801,7 @@
},
{
"cell_type": "code",
- "execution_count": 319,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": []
@@ -1826,7 +1823,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -1840,7 +1837,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.3"
+ "version": "3.10.4"
}
},
"nbformat": 4,
diff --git a/ass01/prediction.txt b/ass01/prediction.csv
