## 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)*

#ai #metrics #deep-learning #machine-learning #statistics