发明名称 INCREMENTAL RESPONSE MODELING
摘要 A method of selecting a one-class support vector machine (SVM) model for incremental response modeling is provided. Exposure group data generated from first responses by an exposure group receiving a request to respond is received. Control group data generated from second responses by a control group not receiving the request to respond is received. A response is either positive or negative. A one-class SVM model is defined using the positive responses in the control group data and an upper bound parameter value. The defined one-class SVM model is executed with the identified positive responses from the exposure group data. An error value is determined based on execution of the defined one-class SVM model. A final one-class SVM model is selected by validating the defined one-class SVM model using the determined error value.
申请公布号 US2014372090(A1) 申请公布日期 2014.12.18
申请号 US201414199409 申请日期 2014.03.06
申请人 SAS Institute Inc. 发明人 Lee Taiyeong;Zhang Ruiwen;Xiao Yongqiao;Dean Jared Langford
分类号 G06F17/50 主分类号 G06F17/50
代理机构 代理人
主权项 1. A non-transitory computer-readable medium having stored thereon computer-readable instructions that when executed by a computing device cause the computing device to: receive exposure group data generated from first responses by an exposure group, wherein the exposure group received a request to respond, wherein a response of the first responses is either positive or negative; receive control group data generated from second responses by a control group, wherein the control group did not receive the request to respond, wherein a response of the second responses is either positive or negative; identify the positive responses in the control group data; identify the positive responses in the exposure group data; (a) define a one-class support vector machine (SVM) model using the identified positive responses from the control group data and an upper bound parameter value; (b) execute the defined one-class SVM model with the identified positive responses from the exposure group data; (c) determine an error value based on execution of the defined one-class SVM; and (d) select a final one-class SVM model by validating the defined one-class SVM model using the determined error value.
地址 Cary NC US