https://github.com/tusharmakkar08/feature_selection_symbiotic

A new approach for feature selection algorithm
https://github.com/tusharmakkar08/feature_selection_symbiotic

Last synced: 25 days ago
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A new approach for feature selection algorithm

• Host: GitHub
• URL: https://github.com/tusharmakkar08/feature_selection_symbiotic
• Owner: tusharmakkar08
• License: mit
• Created: 2014-11-17T16:16:37.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2015-04-23T08:56:54.000Z (over 9 years ago)
• Last Synced: 2023-04-01T12:52:12.644Z (over 1 year ago)
• Language: Python
• Size: 194 KB
• Stars: 1
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.md
  • License: LICENSE.md

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README

        
FEATURE SELECTION USING PAIRWISE SYMBIOTIC EVOLUTION

====================================================

In machine learning and statistics, feature selection, also known as variable selection, attribute

selection or variable subset selection, is the process of selecting a subset of relevant features for

use in model construction. The central assumption when using a feature selection technique is

that the data contains many redundant or irrelevant features. Redundant features are those which

provide no more information than the currently selected features, and irrelevant features provide

no useful information in any context. Thus finding a “compact” subset of non-redundant and

relevant features is an important machine learning problem.We are trying to improvise the

Feature Selection Algorithm by giving more relevant results in the copacetic time period using

pairwise symbiotic evolution.