Analysis of feature selection stability on high dimension and small sample data

DOI10.1016/j.csda.2013.07.012zbMath1471.62050OpenAlexW2061553036WikidataQ62609959 ScholiaQ62609959MaRDI QIDQ1621349

Blaise Hanczar, David Dernoncourt, Jean-Daniel Zucker

Publication date: 8 November 2018

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

Full work available at URL: https://doi.org/10.1016/j.csda.2013.07.012

zbMATH Keywords

stabilitysmall samplefeature selectionlow \(N/D\) ratio

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

Ensemble decision forest of RBF networks via hybrid feature clustering approach for high-dimensional data classification

Uses Software

• UCI-ml

Cites Work

• Unnamed Item
• Robust variable selection through MAVE
• Gene selection for cancer classification using support vector machines

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