Extensions of simple component analysis and simple linear discriminant analysis using genetic algorithms

DOI10.1016/j.csda.2008.03.021zbMath1452.62418OpenAlexW2012806034MaRDI QIDQ1023838

Christelle Reynès, Robert Sabatier

Publication date: 16 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2008.03.021

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Using a genetic algorithm-based RAROC model for the performance and persistence of the funds ⋮ \(rs\)-sparse principal component analysis: a mixed integer nonlinear programming approach with VNS ⋮ Evolutionary Computation Methods and their applications in Statistics

Uses Software

• R
• ElemStatLearn

Cites Work

• Principal component analysis.
• Genetic algorithms: Principles and perpectives. A guide to GA theory
• Simple Component Analysis
• Simple Principal Components
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