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Hands-On Artificial Intelligence with Java for Beginners

You're reading from   Hands-On Artificial Intelligence with Java for Beginners Build intelligent apps using machine learning and deep learning with Deeplearning4j

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789537550
Length 144 pages
Edition 1st Edition
Languages
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Author (1):
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Nisheeth Joshi Nisheeth Joshi
Author Profile Icon Nisheeth Joshi
Nisheeth Joshi
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Table of Contents (9) Chapters Close

Preface 1. Introduction to Artificial Intelligence and Java FREE CHAPTER 2. Exploring Search Algorithms 3. AI Games and the Rule-Based System 4. Interfacing with Weka 5. Handling Attributes 6. Supervised Learning 7. Semi-Supervised and Unsupervised Learning 8. Other Books You May Enjoy

Filtering attributes


We will learn how to filter attributes in this section. Let's start with the code.

We will first import the following packages and classes:

import weka.core.Instances;
import weka.core.converters.ArffSaver;
import java.io.File;
import weka.core.converters.ConverterUtils.DataSource;
import weka.filters.Filter;
import weka.filters.unsupervised.attribute.Remove;

We imported the Instances, ArffSaver, File, and DataSourceclasses from their respective packages, as seen in the preceding code. We used them in the previous chapter, as well. The Instance class will take the database into the memory, and we will work with the dataset in the memory. The ArffSaver class will help us to save our dataset onto the disk. The File class will give the name to the disk, and the DataSource class will open the dataset from the disk.

As you can see in the preceding code snippet, we imported a new class, Filter, from the weka.filters package. We can apply filters using the Filter class. The filter...

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