Article detail · 2011
Effect of dimension reduction by principal component analysis on clustering
Journal of Statistics and Management Systems
YÖKSİS
OpenAlex
Citations 3
Percentile 10.6%
FWCI 0.0
- Year
- 2011
- ISSN
0972-0510- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
English (OpenAlex)
In this empirical study, our goal is to investigate the effectiveness of clustering high dimensional data using principle components (PCs) instead of original variables. Effects of PCs instead original variables on clustering of simulated data sets which have different features are investigated by two different criteria. Moreover in this study we also showed that the effectiveness of clustering high dimensional data using standardized variables instead of original variables.
Topics
- Advanced Clustering Algorithms Research
- Face and Expression Recognition
- Data Mining Algorithms and Applications
Primary topic Advanced Clustering Algorithms Research