Computing Classification Evaluation Metrics in R

by Said Bleik, Shaheen Gauher, Data Scientists at Microsoft Evaluation metrics are the key to understanding how your classification model performs when applied to a test dataset. In what follows, we present a tutorial on how to compute common metrics that are often used in evaluation, in addition to metrics generated from random classifiers, which help in justifying the value added by your predictive model, especially in cases where the common metrics suggest otherwise. Creating the Confusion Matrix Accuracy Per-class Precision, Recall, and F-1 Macro-averaged Metrics One-vs-all Matrices Average Accuracy Micro-averaged Metrics Evaluation on Highly Imbalanced Datasets Majority-class Metrics Random-guess...

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