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Cline: A new decision-tree family

dc.contributor.authorAmasyali, M. Fatih
dc.contributor.authorErsoy, Okan
dc.contributor.institutionauthorAMASYALI, Mehmet Fatih
dc.date.accessioned2026-06-27T13:09:11Z
dc.date.issued2008
dc.description.abstractA new family of algorithm called Cline that provides a number of methods to construct and use multivariate decision trees is presented. We report experimental results for two types of data: synthetic data to visualize the behavior of the algorithms and publicly available eight data sets. The new methods have been tested against 23 other decision-tree construction algorithms based on benchmark data sets. Empirical results indicate that our approach achieves better classification accuracy compared to other algorithms.en
dc.description.urihttps://doi.org/10.1109/tnn.2007.910729
dc.identifier.doi10.1109/tnn.2007.910729
dc.identifier.endpage363
dc.identifier.issn1045-9227
dc.identifier.issue2
dc.identifier.pubmed18269966
dc.identifier.startpage356
dc.identifier.urihttps://hdl.handle.net/20.500.14981/50452
dc.identifier.volume19
dc.identifier.wos000253272100014
dc.language.isoeng
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartofIEEE TRANSACTIONS ON NEURAL NETWORKS
dc.subjectclassifier combination
dc.subjectdecision forests
dc.subjectdecision trees
dc.subjectlearning (artificial intelligence)
dc.subjectmachine learning
dc.subjectmultivariate decision trees
dc.subjectpattern classification
dc.subjectpattern recognition
dc.subjectSELECTION
dc.subjectComputer Science
dc.subjectEngineering
dc.titleCline: A new decision-tree family
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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