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PubMed · 8004148

A support for decision-making: cost-sensitive learning system.

I Bruha·S Kocková
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Abstract

This paper investigates a machine learning (ML) algorithm for supporting a decision-making system that is able to handle diagnostic problems. The input data are expressed by solved cases of patients' diagnoses, and the output is formed by a set of decision rules which may be directly exploited for a decision support. We have chosen the methodology of covering ML algorithms, namely the CN2 algorithm, as a starting point, and designed and implemented a certain extension of CN2 that comprises: advanced discretizing numerical attributes and incorporating attribute cost to economize the classification.

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AlgorithmsArtificial IntelligenceCosts and Cost AnalysisDecision Making, Computer-AssistedDiagnosis, Computer-AssistedHumansMedical OncologyJournal Article

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BibTeXRIS

I Bruha, S Kocková. 1994. A support for decision-making: cost-sensitive learning system.. https://doi.org/10.1016/0933-3657(94)90058-2

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