ROC曲線¶
| タブ | 説明 |
|---|---|
| パフォーマンス | 確率スケール上の任意のポイントで、選択したモデルに関連する分類、パフォーマンス、統計を調べるのに役立ちます。 |
For classification experiments, the ROC Curve tab provides the following tools:
次のステップ¶
Continue evaluating your classification model with these related insights.
- Confusion Matrix: Evaluate model performance for multiclass experiments using a confusion matrix.
- Lift Chart: See how well the model segments the target population and ranks predictions from low to high.
- Metric Scores: Review the model's performance across all supported metrics.