International Journal of Sciences: Basic and Applied Research
Abstract
Principal component Analysis (PCA) is one of the most frequently used multivariate statistical methods. Especially, it is used on the purpose of dimension reduction and obtaining uncorrelated variables. However, classic PCA (CPCA) is sensitive to outlier. Because it is based on classic covariance or correlation matrices influenced by outliers
