Fit vs. Transform in SciKit libraries for Machine LearningData Science by Sunny Srinidhi - November 7, 2019November 7, 20190 We have seen methods such as fit(), transform(), and fit_transform() in a lot of SciKit's libraries. And almost all tutorials, including the ones I've written, only tell you to just use one of these methods. The obvious question that arises here is, what do those methods mean? What do you mean by fit something and transform something? The transform() method makes some sense, it just transforms the data, but what about fit()? In this post, we'll try to understand the difference between the two. To better understand the meaning of these methods, we'll take the Imputer class as an example, because the Imputer class has these methods. But before we get started, keep in mind that fitting something like an imputer
What is Feature Selection and why do we need it in Machine Learning?Data Science by Sunny Srinidhi - July 31, 2018November 11, 20192 If you've come across a dataset in your machine learning endeavors which has more than one feature, you'd have also heard of a concept called Feature Selection. Today, we're going to find out what it is and why we need it. When a dataset has too many features, it would not be ideal to include all of them in our machine learning model. Some features may be irrelevant for the independent variable. For example, if you are going to predict how much it would cost to crush a car, and the features you're given are: the dimensions of the car if the car will be delivered to the crusher or the company has to go pick it up if the car