mirror of
https://github.com/kuhyx/WUT_Computer_Science.git
synced 2026-07-04 14:43:08 +02:00
Add files via upload
This commit is contained in:
parent
4725c4df98
commit
cabc1aa26b
51
main.ipynb
51
main.ipynb
@ -2,7 +2,7 @@
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 57,
|
||||
"execution_count": 71,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
@ -22,7 +22,7 @@
|
||||
"from statistics import median\n",
|
||||
"from sklearn.model_selection import train_test_split\n",
|
||||
"from sklearn.feature_selection import RFE\n",
|
||||
"from sklearn.tree import DecisionTreeRegressor\n",
|
||||
"from sklearn.tree import DecisionTreeRegressor, plot_tree\n",
|
||||
"import numpy as np\n",
|
||||
"from sklearn.metrics import mean_squared_error\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
@ -1483,6 +1483,53 @@
|
||||
"display(X_test[np.abs(y_test - y_pred_test) < 1])\n",
|
||||
"display(X_test['Suma'][np.abs(y_test - y_pred_test) < 1].drop_duplicates().values)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 92,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"0.3391 — Dochody_podatek_od_srodkow_transportowych\n",
|
||||
"0.1816 — Dochody_podatek_od_spadkow\n",
|
||||
"0.1590 — Powierzchnia\n",
|
||||
"0.0714 — Wynagrodzenie_ogolem\n",
|
||||
"0.0675 — Dochody_podatek_lesny\n",
|
||||
"0.0377 — Dochody_razem\n",
|
||||
"0.0312 — Dochody_podatek_rolny\n",
|
||||
"0.0258 — Dochody_z_majatku\n",
|
||||
"0.0220 — Dochody_podatek_PCC\n",
|
||||
"0.0172 — Wynagrodzenie_w_relacji_do_sredniej\n",
|
||||
"0.0172 — Dochody_podatek_od_dzialalnosci_gospodarczej\n",
|
||||
"0.0158 — Dochody_podatek_od_nieruchomosci\n",
|
||||
"0.0144 — Dochody_podatek_odrebne_ustawy\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"selector = RFE(estimator=DecisionTreeRegressor(random_state=0, max_depth=best_params[0]), n_features_to_select=best_params[1])\n",
|
||||
"selector.fit(X, y)\n",
|
||||
"X_selected = selector.transform(X)\n",
|
||||
"\n",
|
||||
"model = DecisionTreeRegressor(random_state=0, max_depth=best_params[0])\n",
|
||||
"model.fit(X_selected, y)\n",
|
||||
"\n",
|
||||
"feature_importance = dict(zip(feature_names, model.feature_importances_))\n",
|
||||
"for feature, importance in sorted(feature_importance.items(), key=lambda x: x[1], reverse=True):\n",
|
||||
" print(f'{importance:.4f} \\u2014 {feature}')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 97,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# plot_tree(model, fontsize=5)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user