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CID3: an extension of ID3 for attributes with ordered domains

Show simple item record Cloete, I Theron, H 2018-05-24T14:07:49Z 2018-05-24T14:07:49Z 1991
dc.identifier.citation Cloete I & Theron H (1991) CID3: an extension of ID3 for attributes with ordered domains. South African Computer Journal. Number 4, 1991 en
dc.identifier.issn 2313-7835
dc.description.abstract Quinlan's ID3 is a popular and efficient algorithm for inducing decision trees from concept examples, where the examples are presented as vectors of attribute-value pairs. If some attributes have integer or real domains ID3 tends to generate very complex decision trees. This is due to: (1) an attribute selection heuristic biased towards attributes with domains of large cardinality (2) strong constraints (bias) imposed on decision trees generated and (3) the fact that ID3 does not distinguish between attributes with unordered domains and attributes with linearly ordered (integer or real) domains. ID3- IV and GID3 address the first and second problem respectively. We propose CID3, a generalization of GID3, which addresses the third problem. These algorithms are compared with respect to five criteria for decision tree quality and computational efficiency. The test domain consists of normal and abnormal electrocardiograms (ECGs) described mainly by integer and real attributes. CID3, which implements the weakest bias and uses the most domain knowledge, generates a superior quality decision tree for the ECGs. en
dc.language en
dc.language.iso en en
dc.publisher South African Institute of Computer Scientists and Information Technologists en
dc.subject Machine learning en
dc.subject Induction en
dc.subject Decision trees en
dc.title CID3: an extension of ID3 for attributes with ordered domains en
dc.type Article en

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