publication . Conference object . Part of book or chapter of book . 2003

Attribute Interactions in Medical Data Analysis

Jakulin, A.; Bratko, I.; Smrke, D.; Demšar, J.; Blaz Zupan;
Open Access
  • Published: 01 Jan 2003
  • Country: Slovenia
Abstract
There is much empirical evidence about the success of naive Bayesian classification (NBC) in medical applications of attribute-based machine learning. NBC assumes conditional independence between attributes. In classification, such classifiers sum up the pieces of class-related evidence from individual attributes, independently of other attributes. The performance, however, deteriorates significantly when the “interactions” between attributes become critical. We propose an approach to handling attribute interactions within the framework of “voting” classifiers, such as NBC. We propose an operational test for detecting interactions in learning data and a procedur...
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free text keywords: Computer and Information Science
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