Precision and Recall in Machine Learning

Original article was published by on Artificial Intelligence on Medium

In Machine Learning, Precision and Recall are the two most important metrics for Model Evaluation. Precision represents the percentage of the results of your model, which are relevant to your model. The recall represents the percentage total of total pertinent results classified correctly by your machine learning algorithm.

In this article, I will show you how you can apply Precision and Recall to evaluate the performance of your Machine Learning model.

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