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Learning Data Mining with Python

You're reading from   Learning Data Mining with Python Use Python to manipulate data and build predictive models

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787126787
Length 358 pages
Edition 2nd Edition
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Concepts
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Toc

Table of Contents (14) Chapters Close

Preface 1. Getting Started with Data Mining FREE CHAPTER 2. Classifying with scikit-learn Estimators 3. Predicting Sports Winners with Decision Trees 4. Recommending Movies Using Affinity Analysis 5. Features and scikit-learn Transformers 6. Social Media Insight using Naive Bayes 7. Follow Recommendations Using Graph Mining 8. Beating CAPTCHAs with Neural Networks 9. Authorship Attribution 10. Clustering News Articles 11. Object Detection in Images using Deep Neural Networks 12. Working with Big Data 13. Next Steps...

A simple classification example

In the affinity analysis example, we looked for correlations between different variables in our dataset. In classification, we have a single variable that we are interested in and that we call the class (also called the target). In the earlier example, if we were interested in how to make people buy more apples, we would explore the rules related to apples and use those to inform our decisions.

You have been reading a chapter from
Learning Data Mining with Python - Second Edition
Published in: Apr 2017
Publisher: Packt
ISBN-13: 9781787126787
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