Deep Learning: Practical Neural Networks with Java

Classification

We will start with the most commonly used machine learning technique, that is, classification. As we reviewed in the first chapter, the main idea is to automatically build a mapping between the input variables and the outcome. In the following sections, we will look at how to load the data, select features, implement a basic classifier in Weka, and evaluate the classifier performance.

Data

For this task, we will have a look at the ZOO database [ref]. The database contains 101 data entries of the animals described with 18 attributes as shown in the following table:

animal	aquatic	fins
hair	predator	legs
feathers	toothed	tail
eggs	backbone	domestic
milk	breathes	cat size
airborne	venomous	type

An example entry in the ...