Unsupervised and Supervised Principal Component Analysis: Tutorial

1 Jun 2019Benyamin GhojoghMark Crowley

This is a detailed tutorial paper which explains the Principal Component Analysis (PCA), Supervised PCA (SPCA), kernel PCA, and kernel SPCA. We start with projection, PCA with eigen-decomposition, PCA with one and multiple projection directions, properties of the projection matrix, reconstruction error minimization, and we connect to auto-encoder... (read more)

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