{
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            "C": 10,
            "class_weight": "balanced",
            "gamma": "scale",
            "kernel": "rbf"
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            "accuracy": 0.54,
            "f1_macro": 0.5244444444444445,
            "roc_auc_ovr": 0.7277777777777779
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        "classification_report": "              precision    recall  f1-score   support\n\n         0.0       0.00      0.00      0.00         2\n         1.0       0.00      0.00      0.00         2\n         2.0       0.33      0.50      0.40         2\n\n    accuracy                           0.17         6\n   macro avg       0.11      0.17      0.13         6\nweighted avg       0.11      0.17      0.13         6\n",
        "roc_auc": 0.4583333333333333,
        "confusion_matrix": [
            [
                0,
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                0
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            [
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                2
            ],
            [
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                1
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    "random_forest": {
        "best_params": {
            "class_weight": "balanced",
            "max_depth": 10,
            "min_samples_split": 2,
            "n_estimators": 200
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        "cv_results": {
            "accuracy": 0.6599999999999999,
            "f1_macro": 0.5755555555555555,
            "roc_auc_ovr": 0.8055555555555556
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        "test_accuracy": 0.19047619047619047,
        "classification_report": "              precision    recall  f1-score   support\n\n         0.0       0.00      0.00      0.00         2\n         1.0       0.00      0.00      0.00         2\n         2.0       0.40      1.00      0.57         2\n\n    accuracy                           0.33         6\n   macro avg       0.13      0.33      0.19         6\nweighted avg       0.13      0.33      0.19         6\n",
        "roc_auc": 0.5,
        "confusion_matrix": [
            [
                0,
                1,
                1
            ],
            [
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                2
            ],
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    "xgboost": {
        "best_params": {
            "colsample_bytree": 0.8,
            "learning_rate": 0.1,
            "max_depth": 3,
            "min_child_weight": 1,
            "n_estimators": 100,
            "subsample": 1.0
        },
        "cv_results": {
            "accuracy": 0.63,
            "f1_macro": 0.5977777777777777,
            "roc_auc_ovr": 0.7722222222222223
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        "test_accuracy": 0.13333333333333333,
        "classification_report": "              precision    recall  f1-score   support\n\n         0.0       0.00      0.00      0.00         2\n         1.0       0.00      0.00      0.00         2\n         2.0       0.33      0.50      0.40         2\n\n    accuracy                           0.17         6\n   macro avg       0.11      0.17      0.13         6\nweighted avg       0.11      0.17      0.13         6\n",
        "roc_auc": 0.5416666666666666,
        "confusion_matrix": [
            [
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}