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Sparse principal component regression for generalized linear models
The basic loss function is based on a combination of the regression loss and PCA loss.
Sparse principal component regression with adaptive loading
Principal component regression (PCR) is a two-stage procedure that selects some principal components and then constructs a regression model regarding them as new explanatory variables.
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