Python: Advanced Guide to Artificial Intelligence

Data preparation

To generate the dataset, we use the  make_regression function from the datasets module of the sklearn library:

from sklearn import datasets as skdsX, y = skds.make_regression(n_samples=200,                            n_features=1,                            n_informative=1,                            n_targets=1,                            noise = 20.0)

This generates a dataset for regression with 200 sample values for one feature and one target each, with some noise added. As we are generating only one target, the function generates y with a one-dimensional NumPy Array; thus, we reshape y to have two dimensions:

if (y.ndim == 1):    y = y.reshape(len(y),1)

We plot the generated dataset to look at the data with the following code:

import matplotlib.pyplot as pltplt.figure(figsize=(14,8))plt.plot(X,y,'b.')plt.title('Original Dataset') ...