Soumik's Tech Blog

 This article was originally published at medium .           To understand the terminologies properly, I will take a simple binary classification problem. Let’s say, our dataset contains the product reviews of an e-commerce website. Each review has a label, either positive (1) or negative (0). Our task is to classify whether a review is positive or negative. Let’s assume, using different NLP techniques, we have made a good/bad model that can predict the labels somehow. For example, the below CSV file snap is the sample of our actual and predicted labels after the prediction that our model made.   fig 1: our sample product review predictions against actual true labels                                               In this dataset, 0 means it’s a negative review, and 1 means it’s a positive review. Here, we got our predicted labels using a machine learning model. I won’t explain any machine learning model or training/testing phase here in this article. If you calculate the tr