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Important Statistical Considerations in Classifier Systems
Bethesda, Maryland March 26-March 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2001.94173414th IEEE Symposium on Computer-Based ...
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James M. DeLeo, National Institutes of Health
Stephen J. Rosenfeld, National Institutes of Health
Abstract: The performance of a classifier system may be limited due to the following: (1) nonmonotonic relationships between individual predictor cofactors and outcomes, (2) prevalence imbalances between development data and application environment data, and (3) failure to account for cost-gain economics. These issues are explored and statistically-based techniques for treating them are presented. In addition, probabilistic and fuzzy interpretations of classifier outputs are discussed, a likelihood ratio transformation of classifier outputs is suggested, and two new cost-gain indexes that rate classifier systems in global economic terms are introduced.
Citation:
James M. DeLeo, Stephen J. Rosenfeld, "Important Statistical Considerations in Classifier Systems," cbms, pp.0285, 14th IEEE Symposium on Computer-Based Medical Systems (CMBS'01), 2001
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