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Metrics.md

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Metrics in ShinyLearner

Background

ShinyLearner Metrics

  • AUROC Area under the ROC curve (the most widely used metric)
  • Accuracy Accuracy
  • BalancedAccuracy Balanced Accuracy
  • Brier Brier Score
  • F1 F1 Score
  • FDR False discovery rate
  • FNR False negative rate
  • FPR False positive rate
  • MCC Matthews correlation coefficient
  • MMCE Mean misclassification error
  • NPV Negative predictive value
  • Precision (Positive predictive value)
  • Recall (sensitivity)
  • TNR True negative rate (specificity)
  • TPR True positive rate (sensitivity)

Additional information

Descriptions from mlr package