The data complexity index to construct an efficient cross-validation method

Cross-validation is a widely used model evaluation method in data mining applications. However, it usually takes a lot of effort to determine the appropriate parameter values, such as training data size and the number of experiment runs, to implement a validated evaluation. This study develops an ef...

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Veröffentlicht in:	Decision Support Systems Jg. 50; H. 1; S. 93 - 102
Hauptverfasser:	Li, Der-Chiang, Fang, Yao-Hwei, Fang, Y.M. Frank
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.12.2010 Elsevier Elsevier Sequoia S.A
Schlagworte:	Applied sciences Binary classification problem Classification Complexity Complexity theory Computer science; control theory; systems Cross-validation Data complexity Data mining Data processing. List processing. Character string processing Dealing Decision support systems Decision theory. Utility theory Exact sciences and technology Mathematical models Mathematics Memory organisation. Data processing Operational research and scientific management Operational research. Management science Optimization Parameter estimation Probability and statistics Sampling techniques Sampling theory, sample surveys Sciences and techniques of general use Software Statistics Studies Training Binary classification problem Data complexity Cross-validation Performance evaluation Data analysis Random sampling Cross validation Data mining Modeling Geometrical model Binary classification
ISSN:	0167-9236, 1873-5797
Online-Zugang:	Volltext
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