A confusion matrix is used in data-mining as a summary of the performance of a classification algorithm.
This crate allows you to create an empty confusion matrix, and then populate it incrementally with the (actual, predicted) results from a data-mining experiment. At any point, various statistical measures and results may be computed.
A confusion matrix is used to record pairs of (actual class, predicted class) as typically produced by a classification algorithm.
Creates a new empty instance of a confusion matrix.