In this experiment we introduce a custom R evaluation module that returns several evaluation metrics to measure a classifier's performance.
This experiment includes a custom R module that allows evaluating a classifier using standard performance evaluation metrics and comparing it to random and majority-class classifiers. The module returns per-class metrics as well as metrics of baseline classifiers: weighted/non-weighted random classifiers and a majority-class classifier. The module expects as input a dataset containing the actual and predicted class labels. The names of those columns can be specified in the properties section. The R code is available at [GitHub]. *Created by a Microsoft employee* : https://github.com/saidbleik/Evaluation