Implementation of FAST Clustering-Based Feature Subset Selection Algorithm for High-Dimensional Data

Smit Shilu; Kushal Sheth; Ekata Mehul

doi:10.1007/978-981-10-0135-2_19

ScienceGate Book Chapters

BOOK-CHAPTER

Implementation of FAST Clustering-Based Feature Subset Selection Algorithm for High-Dimensional Data

Smit Shilu Kushal Sheth Ekata Mehul

Year: 2016 Advances in intelligent systems and computing Pages: 203-213 Publisher: Springer Nature

DOI: 10.1007/978-981-10-0135-2_19

Get Full-Text PDF Get Analytical Report

Keywords:

Cluster analysis Feature selection Computer science Feature (linguistics) Dimensionality reduction Curse of dimensionality Data mining Minimum redundancy feature selection Pattern recognition (psychology) Graph Artificial intelligence Selection (genetic algorithm) Correlation clustering Algorithm Theoretical computer science

Metrics

Cited By

1.07

FWCI (Field Weighted Citation Impact)

Refs

0.60

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Gene expression and cancer classification

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Clustering Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Implementation of FAST Clustering-Based Feature Subset Selection Algorithm for High-Dimensional Data

Metrics

Citation History

Topics

Related Documents

A Fast Clustering-Based Feature Subset Selection Algorithm for High-Dimensional Data

FEATURE SUBSET SELECTION FOR HIGH DIMENSIONAL DATA BASED ON CLUSTERING

EFFICIENT DESIGN OF FAST FEATURE SUBSET SELECTION ALGORITHM FOR MULTI-DIMENSIONAL DATA BASED ON CLUSTERING

EFFICIENT DESIGN OF FAST FEATURE SUBSET SELECTION ALGORITHM FOR MULTI-DIMENSIONAL DATA BASED ON CLUSTERING

Optimal feature subset selection in high dimensional data clustering