Feature selection in threes: Neighborhood relevancy, redundancy, and granularity interactivity

Keyu Liu; Tianrui Li; Xibei Yang; Hengrong Ju; Xin Yang; Dun Liu

doi:10.1016/j.asoc.2023.110679

ScienceGate Book Chapters

JOURNAL ARTICLE

Feature selection in threes: Neighborhood relevancy, redundancy, and granularity interactivity

Keyu Liu Tianrui Li Xibei Yang Hengrong Ju Xin Yang Dun Liu

Year: 2023 Journal: Applied Soft Computing Vol: 146 Pages: 110679-110679 Publisher: Elsevier BV

DOI: 10.1016/j.asoc.2023.110679

Get Full-Text PDF Get Analytical Report

Keywords:

Granularity Interactivity Redundancy (engineering) Computer science Feature selection Data mining Feature (linguistics) Artificial intelligence World Wide Web

Metrics

Cited By

6.49

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Rough Sets and Fuzzy Logic

Physical Sciences → Computer Science → Computational Theory and Mathematics

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Dental Radiography and Imaging

Health Sciences → Dentistry → Oral Surgery

Feature selection in threes: Neighborhood relevancy, redundancy, and granularity interactivity

Metrics

Citation History

Topics

Related Documents

Semi-supervised feature selection by minimum neighborhood redundancy and maximum neighborhood relevancy

Feature selection using max dynamic relevancy and min redundancy

Recursive Feature Selection Based on Minimum Redundancy Maximum Relevancy

A stable feature selection method based on relevancy and redundancy

Fuzzy entropy based Max-Relevancy and Min-Redundancy feature selection