Book Image

Java Data Science Cookbook

By : Rushdi Shams
Book Image

Java Data Science Cookbook

By: Rushdi Shams

Overview of this book

If you are looking to build data science models that are good for production, Java has come to the rescue. With the aid of strong libraries such as MLlib, Weka, DL4j, and more, you can efficiently perform all the data science tasks you need to. This unique book provides modern recipes to solve your common and not-so-common data science-related problems. We start with recipes to help you obtain, clean, index, and search data. Then you will learn a variety of techniques to analyze, learn from, and retrieve information from data. You will also understand how to handle big data, learn deeply from data, and visualize data. Finally, you will work through unique recipes that solve your problems while taking data science to production, writing distributed data science applications, and much more - things that will come in handy at work.
Table of Contents (16 chapters)
Java Data Science Cookbook
About the Author
About the Reviewer
Customer Feedback

Chapter 4. Learning from Data - Part 1

In this chapter, we will cover the following recipes:

  • Creating and saving an Attribute-Relation File Format file
  • Cross-validating a machine-learning model
  • Classifying unseen test data
  • Classifying unseen test data with a filtered classifier
  • Generating linear regression models
  • Generating logistic regression models
  • Clustering data using the KMeans algorithm
  • Clustering data from classes
  • Learning association rules from data
  • Selecting features/attributes using the low-level method, the filtering method, and the meta-classifier method