import fix
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@ -31,14 +31,14 @@
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"import numpy as np\n",
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"import numpy as np\n",
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"import seaborn as sns\n",
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"import seaborn as sns\n",
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"import featuretools as ft\n",
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"import featuretools as ft\n",
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"import time\n",
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"import math\n",
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"from imblearn.over_sampling import RandomOverSampler\n",
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"from imblearn.over_sampling import RandomOverSampler\n",
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"from sklearn.model_selection import train_test_split\n",
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"from sklearn.model_selection import train_test_split\n",
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"import time\n",
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"from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score\n",
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"from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score\n",
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"from sklearn.ensemble import RandomForestClassifier\n",
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"from sklearn.ensemble import RandomForestClassifier\n",
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"from sklearn.model_selection import cross_val_score\n",
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"from sklearn.model_selection import cross_val_score\n",
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"\n",
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"from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error\n",
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"\n",
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"\n",
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"\n",
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"df = pd.read_csv(\"..\\\\static\\\\csv\\\\students_adaptability_level_online_education.csv\")\n",
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"df = pd.read_csv(\"..\\\\static\\\\csv\\\\students_adaptability_level_online_education.csv\")\n",
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"print(df.columns)"
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"print(df.columns)"
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@ -1505,8 +1505,6 @@
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}
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}
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],
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],
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"source": [
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"source": [
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"from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error\n",
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"import math\n",
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"y_pred = model.predict(test_encoded)\n",
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"y_pred = model.predict(test_encoded)\n",
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"\n",
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"\n",
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"# Анализ важности признаков\n",
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"# Анализ важности признаков\n",
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