发明名称 Normalization of predictive model scores
摘要 Methods, systems, and apparatus, including computer programs encoded on computer storage media, for score normalization. One of the methods includes receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output. The method includes generating a first trained predictive model using the initial training data and a training function. The method includes generating intermediate training records by inputting input data of the initial training records to a second trained predictive model, the second trained predictive model generated using the training function, each intermediate training record having a score. The method also includes generating a score normalization model using a score normalization training function and the intermediate training records.
申请公布号 US9406019(B2) 申请公布日期 2016.08.02
申请号 US201313757013 申请日期 2013.02.01
申请人 Google Inc. 发明人 Lin Wei-Hao;Green Travis H. K.;Kaplow Robert;Fu Gang;Mann Gideon S.
分类号 G06N5/02;G06N99/00 主分类号 G06N5/02
代理机构 Fish & Richardson P.C. 代理人 Fish & Richardson P.C.
主权项 1. A computer-implemented method comprising: receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output; generating first intermediate training records by inputting input data of a first subset of the initial training records to a first trained predictive model, the first trained predictive model generated using at least a second subset of the initial training records and a training function, each first intermediate training record having a first score; generating second intermediate training records by inputting input data of the second subset of the initial training records to a second trained predictive model, the second trained predictive model generated using the training function and at least the first subset of the initial training records, each second intermediate training record having a second score; and generating, for the first trained predictive model and the second trained predictive model, a score normalization model using a score normalization training function, the first intermediate training records, and the second intermediate training records.
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