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In QSAR/QSPR modeling, building an accurate partial least squares (PLS) model usually involves descriptor selection, outlier detection, applicability domain assessment, nonlinear relationship, and model stability problems. In the present study, we presented an ensemble PLS (EnPLS) method for solving these modeling tasks under a unified methodology framework. EnPLS aims at developing a consistent algorithmic...
As a representative paradigm of evolutionary algorithms, particle swarm optimization (PSO) has been combined with partial least square (PLS) (called PSO‐PLS) to select informative descriptors in quantitative structure‐activity/property relationship (QSAR/QSPR). However, one of the main limitations of PSO‐PLS is that it ignores PLS model information. In this paper, by incorporating the PLS model information...
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