Java Data Science Cookbook

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

Introduction

In this chapter and the following, chapter we will cover recipes that use machine-learning techniques to learn patterns from data. These patterns are the center of attention for at ...