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Haskell Data Analysis cookbook

You're reading from   Haskell Data Analysis cookbook Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783286331
Length 334 pages
Edition 1st Edition
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Author (1):
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Nishant Shukla Nishant Shukla
Author Profile Icon Nishant Shukla
Nishant Shukla
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Hunt for Data FREE CHAPTER 2. Integrity and Inspection 3. The Science of Words 4. Data Hashing 5. The Dance with Trees 6. Graph Fundamentals 7. Statistics and Analysis 8. Clustering and Classification 9. Parallel and Concurrent Design 10. Real-time Data 11. Visualizing Data 12. Exporting and Presenting Index

Finding maximal cliques in a graph


Haskell comes with a luxury of vital graph libraries, conveniently one of which is the clique detection library from Data.Algorithm.MaximualCliques. A clique in a graph is a subgraph where all the nodes have connections between themselves, and is depicted as follows:

For example, the preceding graph contains two cliques shaded in different colors. Perhaps, the graph represents web pages that link to each other. We can visually infer that there might be two clusters of Internet communities due to the structure of the graph. As the network of connections increases, finding the greatest clique becomes an exponentially difficult problem.

In this recipe, we will use an efficient implementation of the maximal clique problem.

Getting started

Install the clique library using cabal:

$ cabal install maximal-cliques

How to do it...

Write the following code in a new file, which we will name Main.hs:

  1. Import the required library:

    import Data.Algorithm.MaximalCliques
  2. In main...

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