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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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 Joshi Joshi
Author Profile Icon Joshi
Joshi
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Table of Contents (14) Chapters Close

Title Page
Copyright and Credits
Packt Upsell
Contributors
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 1. Other Books You May Enjoy Index

Loading and saving models


Now, we will look at how to save a model that we have trained, and then load that model onto a hard disk. So, let's quickly get to the code.

In this particular section, we'll be saving a model; so, we'll use the following three classes:

import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;
import weka.classifiers.trees.J48;

We'll take the ARFF file into our src object (of the DataSource class), and we'll assign it to the dt object of the Instances class. Then, we'll assign the src object to our dt object; in the dt object, we'll indicate which particular attribute is a class attribute. We'll set certain options for our decision tree classifier, and we'll create an object for our decision tree classifier. Then, we'll set options for it, and we'll build it:

    public static void main(String[] args) {
        // TODO code application logic here
        try {
            DataSource src = new DataSource("/Users/admin/Documents/NetBeansProjects...
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