Evaluation Metric
A quantitative measure of model performance on specific tasks, enabling objective assessment and comparison.
In more detail
Different tasks need different metrics. Classification: accuracy, precision, recall, F1, AUC. Regression: MAE, MSE, RMSE. NLP: BLEU, ROUGE, Perplexity. Choosing appropriate metrics is crucial for correct model assessment.
Examples
- Accuracy for balanced classification
- Precision-Recall for imbalanced data
- BLEU for translation
- Perplexity for language modeling
Related terms
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