python code for the Diabetes dataset

Load the data set, and read the DESCR, features, keys, ..etc.

Select 3 numerical features (attributes)

Extract each one of these attributes into a separate array (make sure to be a column vector)

Split the feature values into training set (400 sample) and testing sets (42 samples), since there are 442 samples (objects).

Create the classifier object (Decision Tree)

Perform the fitting and prediction.

Plot the figures

Repeat for the other 2 features