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Principal Model Analysis Based on Partial Least Squares
[article]
2019
arXiv
pre-print
Motivated by the Bagging Partial Least Squares (PLS) and Principal Component Analysis (PCA) algorithms, we propose a Principal Model Analysis (PMA) method in this paper. In the proposed PMA algorithm, the PCA and the PLS are combined. In the method, multiple PLS models are trained on sub-training sets, derived from the original training set based on the random sampling with replacement method. The regression coefficients of all the sub-PLS models are fused in a joint regression coefficient
arXiv:1902.02422v1
fatcat:554yjf5jmvhc5j6et4vp63m7my