A confusion matrix is a table used to evaluate the performance of a classification model. It is used to measure the accuracy of a model by comparing the predicted values with the actual values. Using ...

The sklearn.metrics module allows for the plotting of a confusion matrix from a classifier (with plot_confusion_matrix), or directly from a pre-computed confusion matrix (with the internal ...

Confusion matrix and classification report are both useful tools for machine learning evaluation and validation, but they serve different purposes for different audiences.