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Machine Learning in Java

You're reading from   Machine Learning in Java Helpful techniques to design, build, and deploy powerful machine learning applications in Java

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788474399
Length 300 pages
Edition 2nd Edition
Languages
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Bostjan Kaluza Bostjan Kaluza
Author Profile Icon Bostjan Kaluza
Bostjan Kaluza
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Toc

Table of Contents (13) Chapters Close

Preface 1. Applied Machine Learning Quick Start FREE CHAPTER 2. Java Libraries and Platforms for Machine Learning 3. Basic Algorithms - Classification, Regression, and Clustering 4. Customer Relationship Prediction with Ensembles 5. Affinity Analysis 6. Recommendation Engines with Apache Mahout 7. Fraud and Anomaly Detection 8. Image Recognition with Deeplearning4j 9. Activity Recognition with Mobile Phone Sensors 10. Text Mining with Mallet - Topic Modeling and Spam Detection 11. What Is Next? 12. Other Books You May Enjoy

Text Mining with Mallet - Topic Modeling and Spam Detection

In this chapter, we'll first discuss what text mining is, what kind of analysis it is able to offer, and why you might want to use it in your application. We'll then discuss how to work with Mallet, a Java library for natural-language processing, covering data import and text pre-processing. Afterward, we will look into two text-mining applications: topic modeling, where we will discuss how text mining can be used to identify topics found in text documents without reading them individually, and spam detection, where we will discuss how to automatically classify text documents into categories.

This chapter will cover the following topics:

  • Introducing text mining
  • Installing and working with Mallet
  • Topic modeling
  • Spam detection
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