So below, we have done preprocessing for our classification dataset.
Now let's learn how to train our modern in Python.
But as you know, before training or model, we need to standardize our data.
So we will use a standard scalar program from a Skillern or prepossessing to do standardizing.
We will first create a sea object which will contain the standardization information, for a word,
independent datasets.
So we are creating a sea object.
We are using Cendon is scalar function and we are using Daudt fake method of dysfunction.
And we are giving our extreme dataset as our training dataset for this Ascender scalar.
Now, using this sended is scalar.
We are transforming our external data and expense data.
And we are asserting this standardized data and to extend standard and x test standard.
Now, to view this data, you can just.
Execute this.
Come on.
First, I have to execute on the above commands, and then if I run this.
You can see that now over duties, Senator, is.
All the variables are almost falling, the same skills and the mean of all the variables is zero and
the variance of all the variables is now equal to one.
We can use this standardized data to create our models.