Wrapper- and Ensemble-Based Feature Subset Selection Methods for Biomarker Discovery in Targeted Metabolomics

Holger Franken; Rainer Lehmann; Hans‐Ulrich Häring; Andreas Fritsche; Norbert Stefan; Andreas Zell

doi:10.1007/978-3-642-24855-9_11

ScienceGate Book Chapters

BOOK-CHAPTER

Wrapper- and Ensemble-Based Feature Subset Selection Methods for Biomarker Discovery in Targeted Metabolomics

Holger Franken Rainer Lehmann Hans‐Ulrich Häring Andreas Fritsche Norbert Stefan Andreas Zell

Year: 2011 Lecture notes in computer science Pages: 121-132 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-642-24855-9_11

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Heuristics Feature selection Discriminative model Artificial intelligence Biomarker discovery Robustness (evolution) Classifier (UML) Pattern recognition (psychology) Machine learning Pareto principle Data mining Mathematics Biology Proteomics Gene

Metrics

Cited By

3.27

FWCI (Field Weighted Citation Impact)

Refs

0.82

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Gene expression and cancer classification

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Metabolomics and Mass Spectrometry Studies

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Bioinformatics and Genomic Networks

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Wrapper- and Ensemble-Based Feature Subset Selection Methods for Biomarker Discovery in Targeted Metabolomics

Metrics

Citation History

Topics

Related Documents

Ensemble feature selection for biomarker discovery in mass spectrometry-based metabolomics

Wrapper Feature Subset Selection for Dimension Reduction Based on Ensemble Learning Algorithm

Ensemble based on GA wrapper feature selection

Ensemble-Based Wrapper Methods for Feature Selection and Class Imbalance Learning

Stability of Filter- and Wrapper-Based Feature Subset Selection