Posts tagged dimensionality-reduction

Principal Component Analysis

• 14 May 2021
Machine Learning
machine-learning pca dimensionality-reduction unsupervised-learning

The Principal Component Analysis (PCA) is a dimension reduction technique widely used. Given a dataset with \(n\) features, the aim is to have \(k\) feature with \(k\le n\) so as the features retain most of the variation present in all of the original variables.

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