ITM Web Conf.
Volume 58, 2024The 6th IndoMS International Conference on Mathematics and Applications (The 6th IICMA 2023)
|Number of page(s)
|09 January 2024
Variance The Estimation Eigen Value of Principal Component Analysis and Nonlinear Principal Component Analysis
1 Faculty of Mathematics and Natural Sciences, Universitas of Halu Oleo, Statistics Department, 2, Southeast Sulawesi, Indonesia
2 Faculty of Mathematics and Natural Sciences, Universitas of Halu Oleo, Computer Science Department, Southeast Sulawesi, Indonesia
* Corresponding author: firstname.lastname@example.org
Nonlinear Principal Component Analysis (PRINCALS) is an extension of Principal Component Analysis (Linear), which can reduce the variables of mixed scale multivariable data (nominal, ordinal, interval, and ratio) simultaneously. This study investigated variance the estimation eigen value of Principal Component Analysis Linear and Nonlinear. The result showed that variance the estimation eigen value of Principal Component Analysis is and variance the estimation eigen value of Nonlinear Principal Component Analysis is Variance the estimation eigen value of Nonlinear Principal Component Analysis better (efficient) than variance the estimation eigen value of Principal Component Analysis.
© The Authors, published by EDP Sciences, 2024
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