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arXiv Machine Learning By Peng Zhao

De-floored Principal Component Regression: When Rank Selection Alone Is Insufficient for Prediction

Read the original on arXiv Machine Learning →

arXiv:2607. 16638v1 Announce Type: cross Abstract: Principal component regression (PCR) regularizes high-dimensional prediction by choosing a spectral cutoff, but rank selection cannot correct systematic inflation of the retained empirical eigenvalues.

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