[FIXED] Difference between fit, transform and fit_transform

Issue

When you import the library from sklearn.preprocessing import StandardScaler, there you have three methods: fit, transform, and fit_transform.

When you should apply fit and transform individually and when at the same time? Could you explain it through an example to clarify it?

Solution

1. You fit your training data, to generalize a model.

2. Then you can apply that model, to any other data to get the prediction. This is like you transform the test data to prediction.

3. if you do fit_transform, you are generalizing a model using training data, and get the result of the model over your training data.

Answered By - alift