Knuth-Morris-Pratt (KMP) Algorithm - Python and Machine Learning for Integrated Circuits - - An Online Book - |
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Python and Machine Learning for Integrated Circuits http://www.globalsino.com/ICs/ | ||||||||
Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= The Knuth-Morris-Pratt (KMP) algorithm is a string-searching algorithm that efficiently finds all occurrences of a pattern (substring) within a text (string). It was developed by Donald Knuth, Vaughan Pratt, and James H. Morris in 1977. The main advantage of the KMP algorithm is its linear time complexity, making it one of the most efficient algorithms for substring searching. It works by precomputing a partial match table (often called the "failure function" or "LPS array") based on the pattern, which allows it to avoid unnecessary character comparisons during the search phase. Note that the KMP algorithm is not a machine learning algorithm. The KMP algorithm is a classic computer science algorithm designed for efficient string matching and does not involve learning from data or making predictions. Table 3807. Process of Knuth-Morris-Pratt (KMP) algorithm.
Knuth-Morris-Pratt (KMP) algorithm for pattern matching in strings and is known for its efficiency in finding occurrences of a pattern in a text. Code: The key characteristic of the KMP algorithm is the construction of the Longest Prefix Suffix (LPS) array, which is used to avoid unnecessary character comparisons when a mismatch occurs. Here's how the script utilizes the KMP algorithm:
The KMP algorithm can be applied to find occurrences of a pattern within a text so that it can be used to find the list of tables in a text file. For instance, this script can be used to find how many sections (tables) there are in a text file. Each section starts with <h5> and ends with </table>. This script finally stores the contents of each section (table) to a different dataframe set as a dataframe table. The content of the text file is: <h5> Sky <a href= … > xyz </a> UVdW </h5> <table> >tbody>
<h5> BMO <a href= 23309 </a> BBHZ </h5> <table> <tbody>
</tbody> </table> Another KMP algorithm which can be used to search all the patterns of the tables (see below) in a webpage file, and then store the tables as dataframes, is the script: In this case, the output from the script is: ============================================
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