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Dimensionality Reduction

2019
Dimensionality reduction is a hot research topic in data analysis today. Thanks to the advances in high-performance computing technologies and in the engineering eld, we entered in the so-called big-data era and an enormous quantity of data is available in every scientificc area, ranging from social networking, economy and politics to e-health and life
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Dimensionality reduction and generalization

Proceedings of the 24th international conference on Machine learning, 2007
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning problems. We show that performing KPCA and then ordinary least squares on the projected data, a procedure known as kernel principal component regression (KPCR), is equivalent ...
MOSCI, SOFIA   +2 more
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