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Author(s): Renáta Bartková, Beloslav Riečan and Anna Tirpáková
Pp: 153-167 (15)
DOI: 10.2174/9781681085388117010008
* (Excluding Mailing and Handling)
In this chapter we compare two methods applied to reduce the dimensionality of data sets. The first method is Principal component analysis, and second method is Factor analysis. We present these methods on data from Atanassov’s intuitionistic fuzzy sets [6]. Earlier we construct an example of applying these methods. The calculations are performed in program R.
Keywords: Principal component analysis, Factor analysis, Atanassov intuitionistic fuzzy sets, Membership function, Non-membership function, Hesitation margin, Correlation, Correlation matrix, Eigenvalues.
Cite this chapter as:
Statistical Applications, Probability Theory for Fuzzy Quantum Spaces with Statistical Applications (2017) 1: 153. https://doi.org/10.2174/9781681085388117010008
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