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{
"best_model_name": "Gradient Boosting",
"best_params_rf": {
"max_depth": 5,
"min_samples_leaf": 2,
"min_samples_split": 10,
"n_estimators": 300
},
"best_params_gb": {
"learning_rate": 0.01,
"max_depth": 3,
"min_samples_split": 2,
"n_estimators": 50
},
"best_params_xgb": {
"learning_rate": 0.01,
"max_depth": 3,
"n_estimators": 100,
"subsample": 1.0
},
"decision_tree": {
"precision": 0.6749498997995992,
"recall": 0.6837190418189201,
"f1": 0.6793061718434853,
"roc_auc": 0.5610423463942246
},
"random_forest": {
"precision": 0.67213612883622,
"recall": 0.8980917580186764,
"f1": 0.7688564476885644,
"roc_auc": 0.6996821658608345
},
"logistic_regression": {
"precision": 0.678694697207405,
"recall": 0.8781973203410475,
"f1": 0.7656637168141593,
"roc_auc": 0.6917604929690724
},
"gradient_boosting": {
"precision": 0.6304069618633222,
"recall": 1.0,
"f1": 0.7733124018838304,
"roc_auc": 0.6856593933709201
},
"xgboost": {
"precision": 0.6487884563027498,
"recall": 0.9675192854242793,
"f1": 0.7767275097783573,
"roc_auc": 0.6896257126244035
}
}