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Code that implements the novel outlier detection algorithms from my Ph.D. dissertation.
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bderenzi/outlier-detect
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outlier-detect (http://github.com/benb111/outlier-detect) Ben Birnbaum ([email protected]) Licensed under Apache (see LICENSE) Python implementions of the Multinomial Model Algorithm (MMA) and the s-Value Algorithm (SVA), as described in B. Birnbaum, B. DeRenzi, A. D. Flaxman, and N. Lesh. Automated quality control for mobile data collection. In DEV ’12, pages 1:1–1:10, 2012. B. Birnbaum. Algorithmic approaches to detecting interviewer fabrication in surveys. Ph.D. Dissertation, Univeristy of Washington, Department of Computer Science and Engineering, 2012. (See http://bbirnbaum.com/pubs.html for PDF versions of these papers.) To use, copy outlierdetect.py into the directory with your code, and import outlierdetect. See the module documentation in outlierdetect.py and example.py for more details. Switch to the 'display' branch on git to use experimental visualization code in outlierdetect.
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Code that implements the novel outlier detection algorithms from my Ph.D. dissertation.
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