Classification Problems
Consider a situation where you have been tasked to build a model to predict whether a product bought by a customer will be returned or not. Since we have focused on regression models so far, let's try and imagine whether these will be the right fit here. A regression model will give continuous values as output (for example, 0.1, 100, 100.25, and so on), but in our case study we just have two values as output – a product will be returned, or it won't be returned. In such a case, except for these two values, all other values will be incorrect/invalid. While we can say that product returned can be considered as the value 0, and product not returned can be considered as the value 1, we still can't define what a value of 1.5 means.
In scenarios like these, classification models come into the picture. Classification problems are the most common type of machine learning problem. Classification tasks are different from regression tasks in the...
