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 |
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Classifier.confusionMatrix() | ConfusionMatrix |
Argument | Type | Details |
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this: classifier | Classifier | The classifier to use. |