7.15 read article How community feedback shapes user behavior

Evaluation Metrics
A binary classifier accuracy,specificity,sensitivety. (accuracy of the entire classifier, correct rate, error rate)
Indicates that the classification is correct:
True Positive: This is a positive example, classified as a positive sample.
True negative: This is a negative sample, which is classified as a negative example.
Indicates a classification error:
False Positive: It is a negative sample, classified into a positive sample, usually called false positives.
False negative: is a positive sample, classified into negative samples, usually called false negatives.

7.15 read article How community feedback shapes user behavior