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  1. [{"about": "Test size: 0.05", "confusion_matrix": [[7, 3], [2, 3]], "classification_report": ["              precision    recall  f1-score   support\n\n           0       0.78      0.70      0.74        10\n           1       0.50      0.60      0.55         5\n\n    accuracy                           0.67        15\n   macro avg       0.64      0.65      0.64        15\nweighted avg       0.69      0.67      0.67        15\n"], "accuracy_score": [0.6666666666666666], "f1_score": 0.5454545454545454, "score": -0.4999999999999997, "values": [0.0, 0.0, -0.6021825396825409, -1.0797297297297273, -0.5481481481481476]}, {"about": "Test size: 0.1", "confusion_matrix": [[19, 2], [7, 1]], "classification_report": ["              precision    recall  f1-score   support\n\n           0       0.73      0.90      0.81        21\n           1       0.33      0.12      0.18         8\n\n    accuracy                           0.69        29\n   macro avg       0.53      0.51      0.50        29\nweighted avg       0.62      0.69      0.64        29\n"], "accuracy_score": [0.6896551724137931], "f1_score": 0.18181818181818182, "score": -0.5967261904761907, "values": [0.0, 0.0, -0.6021825396825409, -1.0797297297297273, -0.5481481481481476]}, {"about": "Test size: 0.25", "confusion_matrix": [[41, 12], [11, 8]], "classification_report": ["              precision    recall  f1-score   support\n\n           0       0.79      0.77      0.78        53\n           1       0.40      0.42      0.41        19\n\n    accuracy                           0.68        72\n   macro avg       0.59      0.60      0.60        72\nweighted avg       0.69      0.68      0.68        72\n"], "accuracy_score": [0.6805555555555556], "f1_score": 0.41025641025641024, "score": -0.6444885799404156, "values": [0.0, 0.0, -0.6021825396825409, -1.0797297297297273, -0.5481481481481476]}, {"about": "Test size: 0.5", "confusion_matrix": [[83, 20], [33, 7]], "classification_report": ["              precision    recall  f1-score   support\n\n           0       0.72      0.81      0.76       103\n           1       0.26      0.17      0.21        40\n\n    accuracy                           0.63       143\n   macro avg       0.49      0.49      0.48       143\nweighted avg       0.59      0.63      0.60       143\n"], "accuracy_score": [0.6293706293706294], "f1_score": 0.208955223880597, "score": -0.8395631067961181, "values": [0.0, 0.0, -0.6021825396825409, -1.0797297297297273, -0.5481481481481476]}]
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