xgboost: 2nd model with grid search and k-fold cross
This commit is contained in:
parent
f5e03cc8d0
commit
e7aac9dabe
@ -128,7 +128,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import numpy as np\n",
|
||||
"from sklearn.model_selection import train_test_split\n",
|
||||
"from sklearn.model_selection import train_test_split,StratifiedKFold, GridSearchCV\n",
|
||||
"from sklearn.metrics import accuracy_score, f1_score, roc_auc_score, classification_report, confusion_matrix\n",
|
||||
"import xgboost as xgb\n",
|
||||
"import joblib\n",
|
||||
@ -248,23 +248,44 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model = xgb.XGBClassifier(\n",
|
||||
"# Basis-Modell\n",
|
||||
"xgb_clf = xgb.XGBClassifier(\n",
|
||||
" objective=\"binary:logistic\",\n",
|
||||
" eval_metric=\"auc\",\n",
|
||||
" learning_rate=0.05,\n",
|
||||
" max_depth=6,\n",
|
||||
" n_estimators=500,\n",
|
||||
" subsample=0.8,\n",
|
||||
" colsample_bytree=0.8,\n",
|
||||
" use_label_encoder=False,\n",
|
||||
" random_state=42\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"model.fit(\n",
|
||||
" X_train, y_train,\n",
|
||||
" eval_set=[(X_val, y_val)],\n",
|
||||
" #early_stopping_rounds=30,\n",
|
||||
" verbose=True\n",
|
||||
")"
|
||||
"# Parameter-Raster\n",
|
||||
"param_grid = {\n",
|
||||
" \"learning_rate\": [0.01, 0.05, 0.1],\n",
|
||||
" \"max_depth\": [4, 6, 8],\n",
|
||||
" \"n_estimators\": [200, 500, 800],\n",
|
||||
" \"subsample\": [0.8, 1.0],\n",
|
||||
" \"colsample_bytree\": [0.8, 1.0]\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"# K-Fold Cross Validation\n",
|
||||
"cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)\n",
|
||||
"\n",
|
||||
"# Grid Search Setup\n",
|
||||
"grid_search = GridSearchCV(\n",
|
||||
" estimator=xgb_clf,\n",
|
||||
" param_grid=param_grid,\n",
|
||||
" scoring=\"roc_auc\",\n",
|
||||
" n_jobs=-1,\n",
|
||||
" cv=cv,\n",
|
||||
" verbose=2\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"# Training mit Cross Validation\n",
|
||||
"grid_search.fit(X_train, y_train)\n",
|
||||
"\n",
|
||||
"print(\"Beste Parameter:\", grid_search.best_params_)\n",
|
||||
"print(\"Bestes AUC:\", grid_search.best_score_)\n",
|
||||
"\n",
|
||||
"# Bestes Modell extrahieren\n",
|
||||
"model = grid_search.best_estimator_"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -272,7 +293,340 @@
|
||||
"execution_count": null,
|
||||
"id": "09a8cd21",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=0.8; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=1.0; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=1.0; total time= 1.1s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.9s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=0.8; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=1.0; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.5s\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Exception ignored in: <function ResourceTracker.__del__ at 0x7f8a96043d80>\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 77, in __del__\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 86, in _stop\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 111, in _stop_locked\n",
|
||||
"ChildProcessError: [Errno 10] No child processes\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=0.8; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=1.0; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.9s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=0.8; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=1.0; total time= 1.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=1.0; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.5s\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Exception ignored in: <function ResourceTracker.__del__ at 0x7f40af477d80>\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 77, in __del__\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 86, in _stop\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 111, in _stop_locked\n",
|
||||
"ChildProcessError: [Errno 10] No child processes\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=0.8; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=1.0; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.9s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=0.8; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=1.0; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.5s\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Exception ignored in: <function ResourceTracker.__del__ at 0x7fd2171ffd80>\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 77, in __del__\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 86, in _stop\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 111, in _stop_locked\n",
|
||||
"ChildProcessError: [Errno 10] No child processes\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=0.8; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=0.8; total time= 1.1s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=6, n_estimators=800, subsample=1.0; total time= 1.0s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.9s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.8s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=0.8; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=0.8; total time= 1.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.01, max_depth=7, n_estimators=800, subsample=1.0; total time= 1.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.6s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.05, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.7s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=5, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=0.8; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=200, subsample=1.0; total time= 0.2s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=6, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=0.8; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=200, subsample=1.0; total time= 0.3s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=0.8; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=500, subsample=1.0; total time= 0.4s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=0.8; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.5s\n",
|
||||
"[CV] END colsample_bytree=1.0, learning_rate=0.1, max_depth=7, n_estimators=800, subsample=1.0; total time= 0.5s\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Exception ignored in: <function ResourceTracker.__del__ at 0x7ff5daf5fd80>\n",
|
||||
"Traceback (most recent call last):\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 77, in __del__\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 86, in _stop\n",
|
||||
" File \"/opt/conda/lib/python3.12/multiprocessing/resource_tracker.py\", line 111, in _stop_locked\n",
|
||||
"ChildProcessError: [Errno 10] No child processes\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from sklearn.metrics import confusion_matrix, accuracy_score, f1_score, roc_auc_score, classification_report, ConfusionMatrixDisplay\n",
|
||||
"\n",
|
||||
@ -325,7 +679,10 @@
|
||||
"source": [
|
||||
"joblib.dump(model, \"xgb_model.joblib\")\n",
|
||||
"joblib.dump(normalizer, \"normalizer.joblib\")\n",
|
||||
"print(\"Model gespeichert.\")"
|
||||
"print(\"Model gespeichert.\")\n",
|
||||
"\n",
|
||||
"model.save_model(\"xgb_model.json\") # als JSON (lesbar, portabel)\n",
|
||||
"model.save_model(\"xgb_model.bin\") # als Binärdatei (kompakt)"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user