USING DATA MINING TO DETECT ANOMALOUS PRODUCER BEHAVIOR: AN ANALYSIS OF SOYBEAN PRODUCTION AND THE FEDERAL CROP INSURANCE PROGRAM

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dc.creatorOlson, Stacey
dc.creatorLittle, Bertis B.
dc.creatorLovell, Ashley C.
dc.date2017-04-01T20:12:15Z
dc.date.accessioned2026-07-09T04:24:52Z
dc.descriptionThe analysis was conducted on the USDA's Risk Management Agency insurance data and NRCS Land Resource Regions from 1994 - 2001 to assist RMA in improving program integrity. The objective is to develop a data-mining algorithm that identifies anomalous producers and counties within LRRs based upon the percentage of acres harvested.
dc.identifierdoi:10.22004/ag.econ.35223
dc.identifierhttps://ageconsearch.umn.edu/record/35223/files/sp03ol05.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/35223
dc.identifier.urihttp://hdl.handle.net/123456789/549555
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/35223
dc.titleUSING DATA MINING TO DETECT ANOMALOUS PRODUCER BEHAVIOR: AN ANALYSIS OF SOYBEAN PRODUCTION AND THE FEDERAL CROP INSURANCE PROGRAM
dc.typeText

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