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Big Data Analytics with Java

You're reading from   Big Data Analytics with Java Data analysis, visualization & machine learning techniques

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787288980
Length 418 pages
Edition 1st Edition
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Author (1):
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RAJAT MEHTA RAJAT MEHTA
Author Profile Icon RAJAT MEHTA
RAJAT MEHTA
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Table of Contents (15) Chapters Close

Preface 1. Big Data Analytics with Java FREE CHAPTER 2. First Steps in Data Analysis 3. Data Visualization 4. Basics of Machine Learning 5. Regression on Big Data 6. Naive Bayes and Sentiment Analysis 7. Decision Trees 8. Ensembling on Big Data 9. Recommendation Systems 10. Clustering and Customer Segmentation on Big Data 11. Massive Graphs on Big Data 12. Real-Time Analytics on Big Data 13. Deep Learning Using Big Data Index

Chapter 7. Decision Trees

Decision trees are one of the simplest (and most popular) of machine learning algorithms, yet they are extremely powerful and used extensively. If you have used a flowchart before, then understanding a decision tree won't be at all difficult for you. A decision tree is a flowchart except in this case, the machine learning algorithm builds this flowchart, for you. Based on the input data, the decision tree algorithm automatically internally creates a knowledge base of a set of rules based on which it can predict an outcome when given a new set of data. In this chapter, we will cover the following topics:

  • Concepts of a decision tree machine learning classifier, including what a decision tree is, how it is built, and how it can be improved
  • The uses of the decision tree
  • A sample case study using decision trees for classification

Let's try to understand the basics of decision trees now.

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