A Summary on Classification Model

  • 1. Evaluation Metrics
  1. Confusion Matrix – predicted class, actual class, accuracy..
  2. Cost Matrix – Just multiply and add corresponded item in the original cost matrix model.
  3. Cost-sensitive Measures – Precision and Recall

Precision and Recall

Precision: what % of tuples that the classifier labeled as positive are actually positive

Recall: what % of positive tuples did the classifier label as positive

F measure – just a harmonic mean of precision and recall. “a measure of a test’s accuracy” (Wikipedia)

A Summary on Classification Model

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