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Machine Learning with scikit-learn Quick Start Guide

You're reading from Machine Learning with scikit-learn Quick Start Guide

Product type Book

Published in Oct 2018

Publisher Packt

ISBN-13 9781789343700

Pages 172 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Kevin Jolly

Table of Contents (10) Chapters

Preface

1. Introducing Machine Learning with scikit-learn

2. Predicting Categories with K-Nearest Neighbors

3. Predicting Categories with Logistic Regression

4. Predicting Categories with Naive Bayes and SVMs

5. Predicting Numeric Outcomes with Linear Regression

6. Classification and Regression with Trees

7. Clustering Data with Unsupervised Machine Learning

8. Performance Evaluation Methods

9. Other Books You May Enjoy

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Support vector machines

In this section, you will learn about support vector machines (SVMs), or, to be more specific, linear support vector machines. In order to understand support vector machines, you will need to know what support vectors are. They are illustrated for you in the following diagram:

The concept of support vectors

In the preceding diagram, the following applies:

The linear support vector machine is a form of linear classifier. A linear decision tree boundary is constructed, and the observations on one side of the boundary (the circles) belong to one class, while the observations on the other side of the boundary (the squares) belong to another class.
The support vectors are the observations that have a triangle on them.
These are the observations that are either very close to the linear decision boundary or have been incorrectly classified.
We can define...

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Authors (1)

Kevin Jolly

Kevin Jolly is a formally educated data scientist with a master's degree in data science from the prestigious King's College London. Kevin works as a statistical analyst with a digital healthcare start-up, Connido Limited, in London, where he is primarily involved in leading the data science projects that the company undertakes. He has built machine learning pipelines for small and big data, with a focus on scaling such pipelines into production for the products that the company has built. Kevin is also the author of a book titled Hands-On Data Visualization with Bokeh, published by Packt. He is the editor-in-chief of Linear, a weekly online publication on data science software and products.

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