lab_3/lab3.ipynb

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