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DTSTAMP:20240428T212157Z
SUMMARY:Dr. Xiaobai Li\, University of Massachusetts Lowell 
DESCRIPTION: \n\nTitle: Predictive Analytics with Strategically Missing Dat
 a\n\nAbstract: We study strategically missing data problems in predictive\
 nanalytics with regression. In many real-world situations\, such as\nfinan
 cial reporting\, college admission\, job application\, and marketing\nadve
 rtisement\, data providers often conceal certain information on\npurpose i
 n order to gain a favorable outcome. It is important for the\ndecision mak
 er to have a mechanism to deal with such strategic\nbehaviors. We propose 
 a novel approach to handle strategically missing\ndata in regression predi
 ction. The proposed method derives imputation\nvalues of strategically mis
 sing data based on the Support Vector\nRegression models. It provides ince
 ntives for the data providers to\ndisclose their true information. We show
  that with the proposed method\nimputation errors for the missing values a
 re minimized under some\nreasonable conditions. An experimental study on r
 eal-world data\ndemonstrates the effectiveness of the proposed approach.\n
 \nRead more about Dr. Li\n[https://www.uml.edu/msb/faculty/li-xiaobai.aspx
 ]\n 
DTSTART:20190517T143000Z
DTEND:20190517T160000Z
LOCATION:Gerri C. LeBow Hall\, 3220 Market Street\, 209\, Philadelphia\, PA
  19104
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