Machine Learning for Healthcare Analytics Projects

Normalizing the dataset

Before we go any further, we need to normalize the information so that the algorithm can read the data consistently:

1. Let's normalize the data using the StandardScaler from the sklearn library. We will import the required tools and fit the data to the scaler using the following lines of code:

from sklearn.preprocessing import StandardScalerscaler = StandardScaler().fit(X)

If we print this scaler, we will get the following output:

Here, we've created a matrix that will do the scaling for us. There are a few different parameters that can be used to scale each of our different columns.

First, however, we have to transform ...