Abstract
Receiver operating characteristic (ROC) methodology evaluates how well a decision strategy classifies retrospective dichotomous or fuzzy events. It also provides a rational basis for designing decision strategies for classifying prospective events. ROCLAB is a public domain software package written in Microsoft QuickBASIC for PC microprocessors that computes ROC functions and their useful derived features for discrete and fuzzy class membership data. Decision strategies that account for uncertainties related to prevalence, false classification costs, and fuzzy class membership are easily constructed with ROCLAB. ROC methodology is explained and ROCLAB features are demonstrated with examples from clinical medicine.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Fuzzy logicReceiver operating characteristicClass (philosophy)Computer scienceData miningDomain (mathematical analysis)SoftwareMachine learningArtificial intelligenceFuzzy setMathematicsProgramming language
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Publication Info
- Year
- 2002
- Type
- article
- Pages
- 318-325
- Citations
- 211
- Access
- Closed
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Cite This
J.M. DeLeo
(2002).
Receiver operating characteristic laboratory (ROCLAB): Software for developing decision strategies that account for uncertainty.
1993 (2nd) International Symposium on Uncertainty Modeling and Analysis
, 318-325.
https://doi.org/10.1109/isuma.1993.366750
Identifiers
- DOI
- 10.1109/isuma.1993.366750