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Ensemble partial least squares regression for descriptor selection, outlier detection, applicability domain assessment, and ensemble modeling in QSAR/QSPR modeling
Author(s) -
Cao DongSheng,
Deng ZhenKe,
Zhu MinFeng,
Yao ZhiJiang,
Dong Jie,
Zhao RuiGang
Publication year - 2017
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2922
Subject(s) - outlier , applicability domain , quantitative structure–activity relationship , partial least squares regression , computer science , stability (learning theory) , ranking (information retrieval) , ensemble forecasting , domain (mathematical analysis) , anomaly detection , artificial intelligence , ensemble learning , data mining , model selection , feature selection , machine learning , mathematics , mathematical analysis
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