Ensemble variable selection using genetic algorithm
Author:
Affiliation:
1. Department of Statistics, Korea University, Korea
2. Department of Information Statistics, Kangwon National University, Korea
Publisher
The Korean Statistical Society
Subject
Applied Mathematics,Statistics, Probability and Uncertainty,Finance,Modeling and Simulation,Statistics and Probability
Link
http://pdf.medrang.co.kr/CSAM/2022/029/CSAM029-06-629.pdf
Reference18 articles.
1. David B, Royston G, Alun J, Jem JR, and Douglas BK (1997). Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry. Analytica Chimica Acta, 348, 71-86.
2. Partha D and Pravin KT (1997). Demand for medical care by the elderly: A finite mixture approach. Journal of applied Econometrics, 12, 313-336.
3. Fan J and Li R (2001). Variable selection via nonconcave penalized likelihood and its oracle properties. Journal of the American Statistical Association, 96, 1348-1360.
4. Leardi R and Gonzalez AL (1998). Genetic algorithms applied to feature selection in PLS regression: how and when to use them. Chemometrics and Intelligent Laboratory Systems, 41, 195-207.
5. Meinshausen N and Bühlmann P (2010). Stability selection. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72, 417-473.
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