Clinical Text Imbalance Benchmark—Results (336 configurations), v2.

This dataset contains per-configuration test metrics for a large-scale benchmark of clinical text classification under extreme class imbalance (49,035 French breast radiology reports; minority prevalence ≈0.33%). A factorial design varied two vectorisers (BoW, TF–IDF), 12 resampling methods plus a baseline, and 15 classifiers. The file ml_experiment_results.csv reports one row per executed configuration (n=336) with: Vectorizer, Sampler, Classifier, Accuracy, Balanced_Accuracy, ROC_AUC, PR_AUC, Precision_male, Recall_male, F1_male, Precision_female, Recall_female, F1_female, F1_macro, F1_weighted, TP, FP, TN, FN.