The Effect of Limited Sample Sets in Pattern Recognition
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Alicia Harris', 'PO_EMAI': None, 'PO_PHON': None}
This research will investigate the effects of limited sample sizes on           the design of statistical pattern recognition systems.  Although an             important and fundamental problem, relatively little is known                   regarding the relationships between dimensionality, distribution, and           the number of samples required to design effective classifiers.  In             practice, use of a finite design set results in classifiers with                performance that is degraded from their potential performance.  The             goals of this research are to (1) provide an analysis of the effect of          the finite sample set on the design of pattern recognition systems,             and (2) to find new classifier design procedures that most effectively          use the available design set, and extend these results to other                 pattern recognition problems such as feature extraction or clustering.
{'FirstName': 'Keinosuke', 'LastName': 'Fukunaga', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Keinosuke Fukunaga', 'EmailAddress': None, 'NSF_ID': '000216138', 'StartDate': '07/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Purdue Research Foundation', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479064353', 'PhoneNumber': '3174946200', 'StreetAddress': '1281 WIN HENTSCHEL BLVD STE 2500', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'C1G1LGYJF5G5', 'ORG_LGL_BUS_NAME': 'PURDUE RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}
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{'Code': '1459', 'Text': 'COMMUNICATIONS SYSTEMS'}
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