A novel feature selection scheme for high-dimensional data sets: four-Staged Feature Selection

DOI10.1080/02664763.2015.1092112OpenAlexW2211726952MaRDI QIDQ5138065

Ayça Çakmak Pehlivanlı

Publication date: 3 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2015.1092112

zbMATH Keywords

classificationdata mininghigh-dimensional datafeature selectionstatistical learningmicroarray gene expressionstatistical filter methods

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Protein sequences, DNA sequences (92D20)

Uses Software

• RONN

Cites Work

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• Feature extraction. Foundations and applications. Papers from NIPS 2003 workshop on feature extraction, Whistler, BC, Canada, December 11--13, 2003. With CD-ROM.
• Theoretical and empirical analysis of ReliefF and RReliefF
• Selection bias in gene extraction on the basis of microarray gene-expression data
• Applied Multivariate Statistical Analysis

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