O'Reilly logo

Regression Analysis with Python by Alberto Boschetti, Luca Massaron

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

An example

We now look at a practical example, containing what we've seen so far in this chapter.

Our dataset is an artificially created one, composed of 10,000 observations and 10 features, all of them informative (that is, no redundant ones) and labels "0" and "1" (binary classification). Having all the informative features is not an unrealistic hypothesis in machine learning, since usually the feature selection or feature reduction operation selects non-related features.

In:
X, y = make_classification(n_samples=10000, n_features=10,
                           n_informative=10, n_redundant=0,
                           random_state=101)

Now, we'll show you how to use different libraries, and different modules, to perform the classification task, using logistic regression. We won't focus here on ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required