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Полина Чубыкина 2024-12-11 21:00:53 +04:00
parent be56e425c9
commit 8c640efcdd
1 changed files with 5 additions and 10 deletions
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lab_4/lab4.ipynb
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@ -365,7 +365,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 12, "execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -392,7 +392,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 13, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -408,7 +408,6 @@
} }
], ],
"source": [ "source": [
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n", "from sklearn.model_selection import train_test_split\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n", "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
"\n", "\n",
@ -437,7 +436,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 14, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -451,16 +450,13 @@
} }
], ],
"source": [ "source": [
"import pandas as pd\n", "\n",
"from scipy import stats\n",
"from sklearn.model_selection import train_test_split, RandomizedSearchCV\n",
"from sklearn.preprocessing import StandardScaler, OneHotEncoder\n", "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
"from sklearn.compose import ColumnTransformer\n", "from sklearn.compose import ColumnTransformer\n",
"from sklearn.pipeline import Pipeline\n", "from sklearn.pipeline import Pipeline\n",
"from sklearn.linear_model import LinearRegression\n", "from sklearn.linear_model import LinearRegression\n",
"from sklearn.tree import DecisionTreeRegressor\n", "from sklearn.tree import DecisionTreeRegressor\n",
"from sklearn.ensemble import GradientBoostingRegressor\n", "from sklearn.ensemble import GradientBoostingRegressor\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
"\n", "\n",
"categorical_features = ['Smoking', 'AlcoholDrinking', 'Stroke', 'DiffWalking', 'Sex', 'AgeCategory', 'Race', 'Diabetic', 'PhysicalActivity', 'GenHealth', 'Asthma', 'KidneyDisease', 'SkinCancer']\n", "categorical_features = ['Smoking', 'AlcoholDrinking', 'Stroke', 'DiffWalking', 'Sex', 'AgeCategory', 'Race', 'Diabetic', 'PhysicalActivity', 'GenHealth', 'Asthma', 'KidneyDisease', 'SkinCancer']\n",
"numeric_features = ['BMI', 'PhysicalHealth', 'MentalHealth']\n", "numeric_features = ['BMI', 'PhysicalHealth', 'MentalHealth']\n",
@ -579,7 +575,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 16, "execution_count": null,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -592,7 +588,6 @@
} }
], ],
"source": [ "source": [
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n", "from sklearn.model_selection import train_test_split\n",
"\n", "\n",
"features = ['BMI', 'Smoking', 'AlcoholDrinking', 'Stroke', 'PhysicalHealth', 'MentalHealth', 'DiffWalking', 'Sex', 'AgeCategory', 'Race', 'Diabetic', 'PhysicalActivity', 'GenHealth', 'Asthma', 'KidneyDisease', 'SkinCancer']\n", "features = ['BMI', 'Smoking', 'AlcoholDrinking', 'Stroke', 'PhysicalHealth', 'MentalHealth', 'DiffWalking', 'Sex', 'AgeCategory', 'Race', 'Diabetic', 'PhysicalActivity', 'GenHealth', 'Asthma', 'KidneyDisease', 'SkinCancer']\n",