Machine Learning in Java - Second Edition

Evaluating classification

Is our classifier doing well? Is this better than the other one? In classification, we count how many times we classify something right and wrong. Suppose there are two possible classification labels of yes and no, then there are four possible outcomes, as shown in the following table:

Predicted as positive?
Yes	No
Really positive?	Yes	TP-True Positive	FN- False Negative
	No	FP- False Positive	TN-True Negative

The four variables:

• True positive (hit): This indicates a yes instance correctly predicted as yes
• True negative (correct rejection): This indicates a no instance correctly predicted as no
• False positive (false alarm): This indicates a no instance predicted as yes
• False negative (miss): This indicates ...