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