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

Making predictions with semi-supervised machine learning models


Now, we'll look into how to make predictions using our trained model. Consider the following code:

import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;
import weka.classifiers.collective.functions.LLGC;
import weka.classifiers.collective.evaluation.Evaluation;

We will be importing two JAR libraries, as follows:

  • The weka.jar library
  • The collective-classification-<date>.jar library

Therefore, we will take the two base classes, Instances and DataSource, and we will use the LLGC class (since we have trained our model using LLGC) from the collective-classifications package, as well as the Evaluation class from the collective-classifications package.

We will first assign an ARFF file to our DataSource object; we'll read it into the memory, in an Instances object. We'll assign a class attribute to our Instances object, and then, we will build our model:

public static void main(String[] args) {
    try{...