Contents Introduction1. Sample selection 2. Dimensionality reduction 2.1. Principal component analysis (PCA)2.2. Independent component analysis (ICA)2.3. Probabilistic principal component analysis (PPCA)2.4. Autoencoder (nonlinear PCA) 2.5. Inverse nonlinear PCA (NLPCA)3. Dividing the data set into the train/valid/test setsConclusionApplication more...
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