Computes a 2D confusion matrix for a classifier based on its training data (ie: resubstitution error). Axis 0 of the matrix correspond to the input classes, and axis 1 to the output classes. The rows and columns start at class 0 and increase sequentially up to the maximum class value, so some rows or columns might be empty if the input classes aren't 0-based or sequential.
| Usage | Returns |
|---|---|
Classifier.confusionMatrix() | ConfusionMatrix |
| Argument | Type | Details |
|---|---|---|
this: classifier | Classifier | The classifier to use. |