Quality Metrics for Multi-class Classification Algorithms

For l classes C1, ..., Cl, given a vector X= (x1, …, xn) of class labels computed at the prediction stage of the classification algorithm and a vector Y= (y1, …, yn) of expected class labels, the problem is to evaluate the classifier by computing the confusion matrix and connected quality metrics: precision, error rate, and so on.

QualityMetricsId for multi-class classification is confusionMatrix.

For more complete information about compiler optimizations, see our Optimization Notice.
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