A strategy that iteratively retains informative variables for selecting optimal variable subset in multivariate calibration

Analytica Chimica Acta

Volumn 807, Issue , 2014, Pages 36-43

  Yun, Yong Huan ^a   Wang, Wei Ting ^a   Tan, Min Li ^a   Liang, Yi Zeng ^a   Li, Hong Dong ^a   Cao, Dong Sheng ^a   Lu, Hong Mei ^a   Xu, Qing Song ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Informative variables; Iteratively retaining informative variables; Partial least squares; Random combination; Variable selection

Indexed keywords

LEAST SQUARES APPROXIMATIONS; MONTE CARLO METHODS;

INFORMATIVE VARIABLES; ITERATIVELY RETAINING INFORMATIVE VARIABLES; PARTIAL LEAST SQUARE (PLS); RANDOM COMBINATION; VARIABLE SELECTION;

ITERATIVE METHODS;

DIESEL FUEL;

ARTICLE; BIOINFORMATICS; CALIBRATION; CLASSIFICATION; GENETIC ALGORITHM; GENOMICS; ITERATIVELY RETAINING INFORMATIVE VARIABLE; MAIZE; MATHEMATICAL VARIABLE; MONTE CARLO METHOD; NEAR INFRARED SPECTROSCOPY; PARTIAL LEAST SQUARES REGRESSION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SAMPLING; SOYBEAN;

INFORMATIVE VARIABLES; ITERATIVELY RETAINING INFORMATIVE VARIABLES; PARTIAL LEAST SQUARES; RANDOM COMBINATION; VARIABLE SELECTION;

ALGORITHMS; CALIBRATION; INTERNET; LEAST-SQUARES ANALYSIS; MODELS, THEORETICAL; MONTE CARLO METHOD; SOFTWARE; SOYBEAN OIL; SPECTROSCOPY, NEAR-INFRARED; WATER; ZEA MAYS;

EID: 84890439287     PISSN: 00032670     EISSN: 18734324     Source Type: Journal    
DOI: 10.1016/j.aca.2013.11.032     Document Type: Article

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