Book Image

Hands-On Artificial Intelligence with Java for Beginners

By : Nisheeth Joshi
Book Image

Hands-On Artificial Intelligence with Java for Beginners

By: Nisheeth Joshi

Overview of this book

Artificial intelligence (AI) is increasingly in demand as well as relevant in the modern world, where everything is driven by technology and data. AI can be used for automating systems or processes to carry out complex tasks and functions in order to achieve optimal performance and productivity. Hands-On Artificial Intelligence with Java for Beginners begins by introducing you to AI concepts and algorithms. You will learn about various Java-based libraries and frameworks that can be used in implementing AI to build smart applications. In addition to this, the book teaches you how to implement easy to complex AI tasks, such as genetic programming, heuristic searches, reinforcement learning, neural networks, and segmentation, all with a practical approach. By the end of this book, you will not only have a solid grasp of AI concepts, but you'll also be able to build your own smart applications for multiple domains.
Table of Contents (14 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Self-training and co-training machine learning models


You will now learn how to develop semi-supervised models.

The very first thing that we'll do is download a package for semi-supervised learning, then we will create a classifier for a semi-supervised model.

Downloading a semi-supervised package

Go to https://github.com/fracpete/collective-classification-weka-package to get the collective-classification Weka package. This is a semi-supervised learning package that is available in Weka.

There are two ways to install the package, as follows:

  • Download the source from GitHub and compile it, then create a JAR file
  • Go to the Weka package manager, and install the collective classification from there

After performing one of the preceding methods, you'll have a JAR file. You will need this JAR file to train the classifier. The source code that we'll be getting will provide the JAR file with the code. Let's look at how this is done.

Creating a classifier for semi-supervised models

Let's start with the following...