2023
DOI: 10.46939/j.sci.arts-23.2-a12
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An Enhanced Classification System Based on Kernel Principal Component Analysis and Data Complexity Measures

Abstract: Principal component analysis is commonly used as a pre-step before employing a classifier to avoid the negative effect of the dimensionality and multicollinearity. The performance of a classifier is severely affected by the deviations from the linearity of the data structure and noisy samples. In this paper, we propose a new classification system that overcomes the drawback of these crucial problems, simultaneously. Our proposal is relying on the kernel principal component analysis with a proper parameter sele… Show more

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