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Machine Learning: End-to-End guide for Java developers

You're reading from   Machine Learning: End-to-End guide for Java developers Data Analysis, Machine Learning, and Neural Networks simplified

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Product type Course
Published in Oct 2017
Publisher Packt
ISBN-13 9781788622219
Length 1159 pages
Edition 1st Edition
Languages
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Authors (2):
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Krishna Choppella Krishna Choppella
Author Profile Icon Krishna Choppella
Krishna Choppella
Uday Kamath Uday Kamath
Author Profile Icon Uday Kamath
Uday Kamath
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Toc

Chapter 3. Basic Algorithms – Classification, Regression, and Clustering

In the previous chapter, we reviewed the key Java libraries for machine learning and what they bring to the table. In this chapter, we will finally get our hands dirty. We will take a closer look at the basic machine learning tasks such as classification, regression, and clustering. Each of the topics will introduce basic algorithms for classification, regression, and clustering. The example datasets will be small, simple, and easy to understand.

The following is the list of topics that will be covered in this chapter:

  • Loading data
  • Filtering attributes
  • Building classification, regression, and clustering models
  • Evaluating models

Before you start

Download the latest version of Weka 3.6 from http://www.cs.waikato.ac.nz/ml/weka/downloading.html.

There are multiple download options available. We'll want to use Weka as a library in our source code, so make sure you skip the self-extracting executables and pick...

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