After the predictive model has been finished, the most important question is: How good is it? Does it predict well? To know about this we have two important metrics called precision and recall. In this article we will learn about these two metrics in brief.
Evaluating the performance of a model is one of the most important stages in predictive modelling, it indicates how successful model has been for the dataset. It enables to tune parameters and in the end test the tuned model against a fresh cut of data. In this article, we will learn about the some of the mostly used methods for testing and validating a machine learning model." " "