- 专利标题: Analytic system based on multiple task learning with incomplete data
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申请号: US15833641申请日: 2017-12-06
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公开(公告)号: US10402741B2公开(公告)日: 2019-09-03
- 发明人: Xin Jiang Hunt , Saba Emrani , Jorge Manuel Gomes da Silva , Ilknur Kaynar Kabul
- 申请人: SAS Institute Inc.
- 申请人地址: US NC Cary
- 专利权人: SAS INSTITUTE INC.
- 当前专利权人: SAS INSTITUTE INC.
- 当前专利权人地址: US NC Cary
- 代理机构: Bell & Manning, LLC
- 主分类号: G06N7/00
- IPC分类号: G06N7/00 ; G06F17/16 ; G06F17/18 ; G06N20/00 ; G16H10/00
摘要:
A computing device computes a weight matrix to predict a value for a characteristic in a scoring dataset. For each of a plurality of related tasks, an augmented observation matrix, a plug-in autocovariance matrix, and a plug-in covariance vector are computed. A weight matrix used to predict the characteristic for each of a plurality of variables and each of a plurality of related tasks is computed. (a) and (b) are repeated with the computed updated weight matrix as the computed weight matrix until a convergence criterion is satisfied: (a) a gradient descent matrix is computed using the computed plug-in autocovariance matrix, the computed plug-in covariance vector, the computed weight matrix, and a predefined relationship matrix, wherein the predefined relationship matrix defines a relationship between the plurality of related tasks, and (b) an updated weight matrix is computed using the computed gradient descent matrix.
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IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06N | 基于特定计算模型的计算机系统 |
G06N7/00 | 基于特定数学模式的计算机系统 |