Random subspace oracle (RSO) ensemble to solve small sample-sized classification problems
Random subspace oracle (RSO) ensemble to solve small sample-sized classification problems
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Publisher
London: Sage Publications Ltd
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Language
English
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Publisher
London: Sage Publications Ltd
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Scope and Contents
Contents
Under certain situations, researchers were forced to work with small sample-sized (SSS) data. With very limited sample size, SSS data have the tendency to undertrain a machine learning algorithm and rendered it ineffective. Some extreme cases in SSS problems will have to deal with large feature-to-instance ratio, where the high number of features c...
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Full title
Random subspace oracle (RSO) ensemble to solve small sample-sized classification problems
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TN_cdi_proquest_journals_2208009225
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2208009225
Other Identifiers
ISSN
1064-1246
E-ISSN
1875-8967
DOI
10.3233/JIFS-18504
