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- [{"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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