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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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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

Searching a string using the Boyer-Moore-Horspool algorithm


When searching for a pattern in a string, we refer to the pattern as the needle and the whole corpus as the haystack. The Horspool string search algorithm implemented in this recipe performs well for almost all pattern lengths and alphabet sizes, but is ideal for large alphabet sizes and large needle sizes. Empirical benchmarks can be found by navigating to the following URL:

http://orion.lcg.ufrj.br/Dr.Dobbs/books/book5/chap10.htm

By preprocessing the query, the algorithm is able to efficiently skip redundant comparisons. In this recipe, we will implement a simplified version called Horspool's algorithm, which achieves the same average best case as the Boyer-Moore algorithm, benefits from having a smaller overhead cost, but may in very rare circumstances suffer the same worst-case running time as the naive search when the algorithm performs too many matches. The Boyer-Moore algorithms should only be used if the extra prepossessing...

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