reports.json

{
  "overall": {
    "at_0.5": {
      "precision_macro": 0.8770778652668416,
      "recall_macro": 0.9213098729227762,
      "f1_macro": 0.8966749265256728,
      "precision_weighted": 0.9386073673306174,
      "recall_weighted": 0.9325153374233128,
      "f1_weighted": 0.9343820254908982,
      "accuracy": 0.9325153374233128,
      "confusion_matrix": [
        [
          124,
          8
        ],
        [
          3,
          28
        ]
      ],
      "classification_report": "              precision    recall  f1-score   support\n\n no-recl (0)     0.9764    0.9394    0.9575       132\n    recl (1)     0.7778    0.9032    0.8358        31\n\n    accuracy                         0.9325       163\n   macro avg     0.8771    0.9213    0.8967       163\nweighted avg     0.9386    0.9325    0.9344       163\n",
      "threshold": 0.5
    },
    "at_best_global": {
      "precision_macro": 0.9260496183206106,
      "recall_macro": 0.9364613880742914,
      "f1_macro": 0.9311364596535698,
      "precision_weighted": 0.9576815904088418,
      "recall_weighted": 0.9570552147239264,
      "f1_weighted": 0.9573144022746298,
      "accuracy": 0.9570552147239264,
      "confusion_matrix": [
        [
          128,
          4
        ],
        [
          3,
          28
        ]
      ],
      "classification_report": "              precision    recall  f1-score   support\n\n no-recl (0)     0.9771    0.9697    0.9734       132\n    recl (1)     0.8750    0.9032    0.8889        31\n\n    accuracy                         0.9571       163\n   macro avg     0.9260    0.9365    0.9311       163\nweighted avg     0.9577    0.9571    0.9573       163\n",
      "threshold": 0.65
    },
    "at_best_by_lang": {
      "precision_macro": 0.9260496183206106,
      "recall_macro": 0.9364613880742914,
      "f1_macro": 0.9311364596535698,
      "precision_weighted": 0.9576815904088418,
      "recall_weighted": 0.9570552147239264,
      "f1_weighted": 0.9573144022746298,
      "accuracy": 0.9570552147239264,
      "confusion_matrix": [
        [
          128,
          4
        ],
        [
          3,
          28
        ]
      ],
      "classification_report": "              precision    recall  f1-score   support\n\n no-recl (0)     0.9771    0.9697    0.9734       132\n    recl (1)     0.8750    0.9032    0.8889        31\n\n    accuracy                         0.9571       163\n   macro avg     0.9260    0.9365    0.9311       163\nweighted avg     0.9577    0.9571    0.9573       163\n",
      "thresholds_by_lang": {
        "it": 0.65
      }
    }
  },
  "thresholds": {
    "global_best": {
      "threshold": 0.65,
      "f1_macro": 0.9311364596535698,
      "precision_macro": 0.9260496183206106,
      "recall_macro": 0.9364613880742914
    },
    "by_lang_best": {
      "it": {
        "threshold": 0.65,
        "f1_macro": 0.9311364596535698,
        "precision_macro": 0.9260496183206106,
        "recall_macro": 0.9364613880742914
      }
    },
    "default": 0.5
  },
  "per_lang": {
    "at_0.5": [
      {
        "lang": "it",
        "n": 163,
        "accuracy": 0.9325153374233128,
        "f1_macro": 0.8966749265256728,
        "precision_macro": 0.8770778652668416,
        "recall_macro": 0.9213098729227762,
        "f1_weighted": 0.9343820254908982,
        "precision_weighted": 0.9386073673306174,
        "recall_weighted": 0.9325153374233128
      }
    ],
    "at_best_global": [
      {
        "lang": "it",
        "n": 163,
        "accuracy": 0.9570552147239264,
        "f1_macro": 0.9311364596535698,
        "precision_macro": 0.9260496183206106,
        "recall_macro": 0.9364613880742914,
        "f1_weighted": 0.9573144022746298,
        "precision_weighted": 0.9576815904088418,
        "recall_weighted": 0.9570552147239264
      }
    ],
    "at_best_by_lang": [
      {
        "lang": "it",
        "n": 163,
        "accuracy": 0.9570552147239264,
        "f1_macro": 0.9311364596535698,
        "precision_macro": 0.9260496183206106,
        "recall_macro": 0.9364613880742914,
        "f1_weighted": 0.9573144022746298,
        "precision_weighted": 0.9576815904088418,
        "recall_weighted": 0.9570552147239264
      }
    ]
  }
}