ensemble_config.json

{
  "proposed_model": "LCVC-Ensemble",
  "full_name": "Leakage-Controlled Validation-Calibrated Multi-Backbone Ensemble",
  "task": "Brain tumor MRI four-class classification",
  "classes": [
    "glioma",
    "meningioma",
    "notumor",
    "pituitary"
  ],
  "num_classes": 4,
  "image_size": 224,
  "preprocessing": {
    "input_mode": "RGB",
    "resize": [
      224,
      224
    ],
    "normalization_mean": [
      0.485,
      0.456,
      0.406
    ],
    "normalization_std": [
      0.229,
      0.224,
      0.225
    ]
  },
  "ensemble_rule": "weighted_average_of_temperature_scaled_softmax_probabilities",
  "selection_rule": "highest validation Macro-F1 among predeclared ensembles; no test labels used for selection",
  "strategy": "top5_by_checkpoint_val_macro_f1",
  "calibrated_probs": true,
  "weight_mode": "uniform",
  "num_members": 5,
  "members": [
    {
      "member_order": 0,
      "model": "convnext_tiny",
      "display_name": "ConvNeXt-Tiny",
      "seed": 123,
      "weight": 0.2,
      "temperature": 1.3677136307807327,
      "checkpoint_file": "best_convnext_tiny_seed123.pt",
      "checkpoint_val_macro_f1": 0.9870486143666763,
      "test_cal_macro_f1": 0.9747367912288595
    },
    {
      "member_order": 1,
      "model": "efficientnet_b0",
      "display_name": "EfficientNet-B0",
      "seed": 123,
      "weight": 0.2,
      "temperature": 1.3258544405019956,
      "checkpoint_file": "best_efficientnet_b0_seed123.pt",
      "checkpoint_val_macro_f1": 0.9842404596100688,
      "test_cal_macro_f1": 0.984111907683999
    },
    {
      "member_order": 2,
      "model": "efficientnet_b0",
      "display_name": "EfficientNet-B0",
      "seed": 2026,
      "weight": 0.2,
      "temperature": 1.2086706764615134,
      "checkpoint_file": "best_efficientnet_b0_seed2026.pt",
      "checkpoint_val_macro_f1": 0.9842174297345077,
      "test_cal_macro_f1": 0.9802870622455948
    },
    {
      "member_order": 3,
      "model": "efficientnet_b0",
      "display_name": "EfficientNet-B0",
      "seed": 42,
      "weight": 0.2,
      "temperature": 1.4470591581130952,
      "checkpoint_file": "best_efficientnet_b0_seed42.pt",
      "checkpoint_val_macro_f1": 0.9835034785528444,
      "test_cal_macro_f1": 0.9859513817770005
    },
    {
      "member_order": 4,
      "model": "convnext_tiny",
      "display_name": "ConvNeXt-Tiny",
      "seed": 42,
      "weight": 0.2,
      "temperature": 1.0611162444290951,
      "checkpoint_file": "best_convnext_tiny_seed42.pt",
      "checkpoint_val_macro_f1": 0.9824939017733962,
      "test_cal_macro_f1": 0.9831484695235262
    }
  ],
  "validation_metrics": {
    "accuracy": 0.9916201117318436,
    "macro_f1": 0.9917075605938603,
    "balanced_accuracy": 0.9916862142328199,
    "macro_auc_ovr": 0.9997306138031021
  },
  "test_metrics": {
    "accuracy": 0.9887640449438202,
    "macro_f1": 0.9887621278421996,
    "balanced_accuracy": 0.9887638076313365,
    "macro_auc_ovr": 0.9997131229291261
  },
  "medical_disclaimer": "This app is for research and educational demonstration only. It is not a medical device and must not be used for diagnosis, treatment, or clinical decision-making."
}