Principal Components Analysis Based on a Fuzzy Sets Approach
نویسنده
چکیده
As with any other multivariate statistical method, Principal Components Analysis is sensitive to outliers, missing data, and poor linear correlation between variables due to poorly distributed variables. As a result data transformations have a large impact upon PCA. This paper introduces a powerful approach to improve PCA: robust fuzzy PCA algorithm (FPCA). The matrix data is fuzzified, thus diminishing the influence of the outliers.
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