Predict
Performance and Training Settings:
Test Loss: 1.1184475421905518
Validation Loss: 1.1013705730438232
Training Loss: 1.2275012731552124
Test Accuracy: 0.4
Precision: 0.25
Recall: 0.16666666666666666
F1 Score: 0.19999999999999998
AUC: 0.4965277777777778
Per Class Precision: 0.00000, 0.75000, 0.00000
Per Class Recall: 0.00000, 0.50000, 0.00000
Per Class F1 Score: 0.00000, 0.60000, 0.00000
Per Class AUC: 0.52778, 0.44444, 0.50000
Data Counts (n): 46, 98, 4
Outcome: c, d, b
Predictors (n): Predictor: revasc, Mean: 0.78992, SD: 0.36652; Predictor: major_amputations, Mean: 0.06667, SD: 0.22537; Predictor: death, Mean: 0.65600, SD: 1.68670
L2 Regularization: 0.01
Number of Epochs: 173
Initial Learning Rate: 0.001
Batch Size: 32
Confusion Matrix:
Training and Validation Logs:
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