Confusion matrix is one of the parameter of measuring accuracy of model or how well model is performing
True Positive-When model predicts positive and it is actually true.
True Negative-When model predicts negative and it is actually true.
Observed/Predicted | 0 | 1 |
0 | TRUE POSITIVE | FALSE NEGATIVE |
1 | FALSE POSITIVE | TRUE NEGATIVE |
False Positive-When model predicts positive and it is incorrect.
False Negative-When model predicts negative and it is incorrect.