Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications

Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications by Muhammad Summair Raza, Usman Qamar.

This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool f...

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Bibliographic Details
Main Authors: Raza, Muhammad Summair (Author), Qamar, Usman (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2019.
Edition:2nd ed. 2019.
Series:Springer eBook Collection.
Subjects:
Artificial intelligence.
Application software.
Database management.
Data mining.
Numerical analysis.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Introduction to Feature Selection
  • Background
  • Rough Set Theory
  • Advance Concepts in Rough Set Theory
  • Rough Set Theory Based Feature Selection Techniques
  • Chapter 6: Unsupervised Feature Selection using RST
  • Critical Analysis of Feature Selection Algorithms
  • Dominance based Rough Set Approach
  • Fuzzy Rough Sets
  • Introduction to classicial Rough Set Based APIs Library
  • Dominance Based Rough Set APIs library.

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