Book Image

Java Data Analysis

By : John R. Hubbard
Book Image

Java Data Analysis

By: John R. Hubbard

Overview of this book

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks. This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs. By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.
Table of Contents (20 chapters)
Java Data Analysis
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
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 library was added in steps 9-10.