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Data Science Algorithms in a Week

You're reading from   Data Science Algorithms in a Week Top 7 algorithms for scientific computing, data analysis, and machine learning

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789806076
Length 214 pages
Edition 2nd Edition
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Authors (2):
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David Toth David Toth
Author Profile Icon David Toth
David Toth
David Natingga David Natingga
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David Natingga
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Toc

Table of Contents (12) Chapters Close

Preface 1. Classification Using K-Nearest Neighbors 2. Naive Bayes FREE CHAPTER 3. Decision Trees 4. Random Forests 5. Clustering into K Clusters 6. Regression 7. Time Series Analysis 8. Python Reference 9. Statistics 10. Glossary of Algorithms and Methods in Data Science
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Clustering into K Clusters

Clustering is a technique for dividing data into clusters, with the same features in the same cluster.

In this chapter, we will cover the following topics:

  • How to use the k-means clustering algorithm, using an example involving household incomes
  • How to classify features by clustering them first with the features, along with the known classes, using an example of gender classification 
  • How to implement the k-means clustering algorithm in Python in the Implementation of k-means clustering algorithm section
  • An example of house ownership and how to choose an appropriate number of clusters for your analysis
  • How to use the example of house ownership to scale a given set of numerical data appropriately to improve the accuracy of classification by using a clustering algorithm
  • An understanding of how different numbers of clusters alter the meaning...
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