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• Published Subscription 17 May 2018

  Principal Component Analysis for Outlier Detection

  By S. Stephen Raj, K. Senthamarai Kannan, K. Manoj

  Abstract: Principal Components Analysis (PCA) is one of the well-known and frequently used multivariate exploratory data analyses. PCA is concerned with analyzing and understanding data in high dimensions, that is to say, PCA method analyzes data sets that represent observations which are identified by several dependent variables that are inter-correlated. Multidimensional scaling (MDS) is a technique that makes a map displaying the comparative attitudes of a number of objects or cases, …

  Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 62s–68s Read article →