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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis 2. Data Preprocessing FREE CHAPTER 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

The Weka libraries

The Weka platform of data analysis implementations is maintained by computer scientists at the University of Waikato in New Zealand. It includes some Java libraries that we have used in this book. For example, the TestDataSource program, shown in Listing 7-5, uses several classes from the weka.core package.

Download Weka from http://www.cs.waikato.ac.nz/ml/weka/downloading.html. The bundle includes the Weka app itself and a folder (weka-3-9-1, as of August, 2017) of Java libraries. Inside the folder you will find the weka.jar file and a folder named doc.

To add the Weka library to NetBeans, follow the same steps 1-8 described previously for adding the Apache Commons Math library, except with weka.jar instead of commons-math3-3.6.1.jar. You can name the library Weka 3.9.1 (or anything you like). For Classpath, add the weka.jar file. For Javadoc, add the doc folder. Then you can add that Weka 3.9.1 library to any NetBeans project the same way that the Apache Commons Math...

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