Evaluation metrics for classification
Accuracy/Error rate
ACC = (TP+TN)/(P+N)
ERR = (FP+FN)/(P+N) = 1-ACC
Confusion matrix
Precision/Recall/F1
Precision = TP/(TP+FP)-- positive predictive value
Recall= TP/(TP+FN) -- true positive rate
F1=1/(1/precision+1/recall)
ROC
True positive rate (TPR): the ratio of positive instances that are correctly classified as positive
TPR = TP/(TP+FN) = recall
True negative rate (TNR): the ratio of negative instances that are correctly classified as negative
TNR = TN/(TN+FP) = specify
False positive rate (FPR): the ratio of negative instances that are incorrectly classified as positive.
FPR = FN/(TN+FP) = 1-specify
ROC: TPR vs FPR
Matthews correlation coefficient
Logarithm loss/cross entropy
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