Effect of dimension reduction by principal component analysis on clustering
Murat Erişoğlu, Ülkü ERİŞOĞLU, Sadullah Sakallıoğlu · Journal of Statistics and Management Systems · 2011
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.