# Confusion Matrix

Are you confused by the confusion matrix? This should help:

Generally:

• Each row represents an actual class.
• Each column represents a predicted class.
• For the rows and columns:
• Start with 0 coz NO = 0.
• End with 1 coz YES = 1.
• i.e. think in ascending order (zero ➔ one).

Regarding each of the 4 elements in the confusion matrix:

• True Positives (TP): These are cases in which we predicted yes (they have the disease), and they do have the disease.
• True Negatives (TN): We predicted no, and they don't have the disease.
• False Positives (FP): We predicted yes, but they don't actually have the disease. (Also known as a Type I error.)
• False Negatives (FN): We predicted no, but they actually do have the disease. (Also known as a Type II error.)

Check out Kevin's Simple Guide to Confusion Matrix for more details.

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#### Jovian Lin, Ph.D.

A Singaporean with a fiery passion in solving real-life problems with machine learning and intelligent hacks.