Confusion Matrix

Confusion Matrix

Actual/Predicted	Negative	Positive
Negative	TN	FP
Positive	FN	TP

• Accuracy
• fraction of correctly identified positives & negatives
  = TP + TN / TP+TN+FP+FN
• Sensitivity/ Recall / Hit Rate / True Positive Rate (TPR) 
• # of actual Yeses correctly predicted / Total # of actual Yeses
  = TP / (TP+FN)
• Specificity / Selectivity / True Negative Rate (TNR) 
• # of actual No's correctly predicted / Total # of actual Nos
  = TN / (TN+FP)
• Precision / Positive Predictive Value
• Probability that a predicted Yes is actually a Yes.
  = TP / (TP+FP)
• Score=400+(20∗log(odds)log(2))

• More metrics.