Class prediction for high-dimensional class-imbalanced data

Background The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the variables available for each subject: the main characteristic of high-dimensional data is that the number of variables greatly...

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Veröffentlicht in:	BMC bioinformatics Jg. 11; H. 1; S. 523
Hauptverfasser:	Blagus, Rok, Lusa, Lara
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 20.10.2010 Springer Nature B.V BMC
Schlagworte:	Algorithms Bioinformatics Biomedical and Life Sciences Breast cancer Breast Neoplasms - classification Breast Neoplasms - genetics Classification Classification - methods Computational Biology/Bioinformatics Computer Appl. in Life Sciences Databases, Factual Discriminant analysis Female Gene Expression Profiling - methods Humans Life Sciences Microarrays Oligonucleotide Array Sequence Analysis - methods Research Article Studies Transcriptome analysis Classification Rule Variable Selection Predictive Accuracy Minority Class Class Imbalance
ISSN:	1471-2105, 1471-2105
Online-Zugang:	Volltext
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