Building a Deployable ML Classifier in Python – Towards Data Science

As visible from the snapshot, data values are quite deviated at some attributes. It is a good practice to standardize the values as it will bring the variance to a reasonable level. Also, since most of the algorithms are using euclidean distance in background, having scaled features is better in model building. Here fit_transform is used so that the StandardScaler will fit on X_data and transform X_data too. If you need to fit and transform it on two different data set, you can call fit and transform function separately too.