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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
Languages
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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

Implementing a min-heap data structure


A heap is a binary tree with both a shape property and a heap property. The shape property enforces the tree to behave in a balanced way by defining each node to have two children unless the node is in the very last level. The heap property ensures that each node is less than or equal to either of its child nodes if it is a min-heap, and vice versa in case of a max-heap.

Heaps are used for constant time lookups for maximum or minimum elements. We will use a heap in the next recipe to implement our own Huffman tree.

Getting started

Install the lens library for easy data manipulation:

$ cabal install lens

How to do it...

  1. Define the MinHeap module in a file MinHeap.hs:

    module MinHeap (empty, insert, deleteMin, weights) where
    
    import Control.Lens (element, set)
    import Data.Maybe (isJust, fromJust)
  2. We will use a list to represent a binary tree data structure for demonstration purposes only. It is best to implement the heap as an actual binary tree (as we have...

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