reports/metrics.json

{
  "n_samples": 997,
  "n_train_original": 797,
  "n_external": 38000,
  "n_train_fit": 38797,
  "n_test": 200,
  "positive_rate": 0.46038114343029085,
  "train_metrics": {
    "accuracy": 0.7314930991217063,
    "precision": 0.6917293233082706,
    "recall": 0.7520435967302452,
    "f1": 0.720626631853786
  },
  "test_metrics": {
    "accuracy": 0.71,
    "precision": 0.660377358490566,
    "recall": 0.7608695652173914,
    "f1": 0.7070707070707071
  },
  "gaps": {
    "precision": 0.031351964817704636,
    "f1": 0.013555924783078876,
    "accuracy": 0.021493099121706383,
    "recall": 0.008825968487146119
  },
  "gap_constraint": 0.05,
  "gap_ok": true,
  "confusion_matrix_test": [
    [
      72,
      36
    ],
    [
      22,
      70
    ]
  ],
  "is_ensemble": true,
  "config": {
    "augment_multiplier": 0.0,
    "lr_C": 0.3057497042744256,
    "max_df": 0.8538283755028163,
    "max_features": 2500,
    "min_df": 4,
    "nb_alpha": 1.006373215225186,
    "ngram_range": "bigram",
    "rf_max_depth": 28,
    "rf_n_estimators": 250
  }
}