(feature_names: Sequence[str], per_feature_values: Sequence[Sequence[float]])
| 244 | |
| 245 | raise ValueError("scoring must be one of: neg_log_loss, accuracy, f1") |
| 246 | |
| 247 | |
| 248 | def _mean(values: Sequence[float]) -> float: |
| 249 | return sum(values) / len(values) if values else 0.0 |
| 250 | |
| 251 | |
| 252 | def _std(values: Sequence[float]) -> float: |
| 253 | if len(values) < 2: |
| 254 | return 0.0 |
| 255 | m = _mean(values) |
| 256 | var = sum((v - m) ** 2 for v in values) / (len(values) - 1) |
| 257 | return sqrt(var) |
| 258 | |
| 259 | |
| 260 | def _importance_table(feature_names: Sequence[str], per_feature_values: Sequence[Sequence[float]]) -> pl.DataFrame: |
no test coverage detected