Introduction

In the first part of this post, I provided an introduction to 10 metrics used for evaluating classification and regression models. In this part, I am going to provide an introduction to the metrics used for evaluating models developed for ranking (AKA learning to rank), as well as metrics for statistical models. In particular, I will cover the talk about the below 5 metrics:

• Mean reciprocal rank (MRR)
• Precision at k
• DCG and NDCG (normalized discounted cumulative gain)
• Pearson correlation coefficient
• Coefficient of determination (R²)

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