Fig. 5.

Confusion matrix for the proposed stacked ensemble model. The matrix describes the detailed test set performance of the classifier by comparing how each case was predicted against their true labels. From this matrix we can easily see that there are 94 true negatives, 11 false positives, 16 false negatives and 82 true positives.