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

• Κύριοι συγγραφείς: Raza, Muhammad Summair (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Qamar, Usman (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Έκδοση: 2nd ed. 2019.
• Θέματα: Artificial intelligence.; Application software.; Database management.; Data mining.; Numerical analysis.; Artificial Intelligence.; Information Systems Applications (incl. Internet).; Database Management.; Data Mining and Knowledge Discovery.; Numeric Computing.

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...

Πίνακας περιεχομένων:

• 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.