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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
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Author (1):
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 Shams Shams
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Shams
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Toc

Table of Contents (16) Chapters Close

Java Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
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

Conducting a Kolmogorov-Smirnov test


The Kolmogorov-Smirnov test (or simply KS test) is a test of equality for one-dimensional probability distributions that are continuous in nature. It is one of the popular methods to determine whether two sets of data points differ significantly.

How to do it...

  1. Create a method that takes two different data distributions. We will see if the difference of the two data distributions is significant by using Kolmogorov-Smirnov test:

            public void calculateKs(double[] x, double[] y){ 
    
  2. One of the key statistics in the test is d-statistic. It is a double value that we will need in order to calculate the p-value of the test:

            double d = TestUtils.kolmogorovSmirnovStatistic(x, y); 
    
  3. To evaluate the null hypothesis that the values are drawn from a unit normal distribution, use the following code:

            System.out.println(TestUtils.kolmogorovSmirnovTest(x, y, 
              false)); 
    
  4. Finally, the p-value of the significance test can be found...

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