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Java Data Science Cookbook

You're reading from   Java Data Science Cookbook Explore the power of MLlib, DL4j, Weka, and more

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787122536
Length 372 pages
Edition 1st Edition
Languages
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Author (1):
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Rushdi Shams Rushdi Shams
Author Profile Icon Rushdi Shams
Rushdi Shams
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Toc

Table of Contents (10) Chapters Close

Preface 1. Obtaining and Cleaning Data FREE CHAPTER 2. Indexing and Searching Data 3. Analyzing Data Statistically 4. Learning from Data - Part 1 5. Learning from Data - Part 2 6. Retrieving Information from Text Data 7. Handling Big Data 8. Learn Deeply from Data 9. Visualizing Data

Creating a linear regression model with MLib


In this recipe, you will see how you can use a linear regression model to model with MLib.

Getting ready

  1. You will be using the Maven project you created in the recipe named Solving simple text mining problems with Apache Spark. If you have not done so yet, then follow steps 1-6 in the Getting ready section of that recipe.

  2. Go to https://github.com/apache/spark/blob/master/data/mllib/ridge-data/lpsa.data, download the data, and save as lr-data.txt in the data folder of your project that you created by following the instruction in step 1. Alternatively, you can create a text file named lr-data.txt in the data folder of your project and copy-paste the data from the aforementioned URL.

  3. In the package that you created, create a Java class file named LinearRegressionMlib.java. Double-click to start writing your code in it.

Now, you are ready to do some coding.

How to do it...

  1. Create a class named LinearRegressionMlib:

            public class LinearRegressionMlib...
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