You're reading from scikit-learn Cookbook - Second Edition

Product typeBook

Published inNov 2017

Reading LevelIntermediate

PublisherPackt

ISBN-139781787286382

Edition2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1)

Trent Hauck

Classifying data with a linear SVM

In the first chapter, we saw some examples of classification with SVMs. We focused on SVMs' slightly superior classification performance compared to logistic regression, but for the most part, we left SVMs alone.

Here, we will focus on them more closely. While SVMs do not have an easy probabilistic interpretation, they do have an easy visual-geometric one. The main idea behind linear SVMs is to separate two classes with the best possible plane.

Let's linearly separate two classes with an SVM.

Getting ready

Let us start by loading and visualizing the iris dataset available in scikit-learn:

...

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scikit-learn Cookbook - Second Edition

Published in: Nov 2017Publisher: PacktISBN-13: 9781787286382

Author (1)

Trent Hauck

Trent Hauck is a data scientist living and working in the Seattle area. He grew up in Wichita, Kansas and received his undergraduate and graduate degrees from the University of Kansas. He is the author of the book Instant Data Intensive Apps with pandas How-to, Packt Publishing—a book that can get you up to speed quickly with pandas and other associated technologies.
Read more about Trent Hauck

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