发明授权
- 专利标题: System and method for scalable cost-sensitive learning
- 专利标题(中): 可扩展成本敏感学习的系统和方法
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申请号: US12690502申请日: 2010-01-20
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公开(公告)号: US07904397B2公开(公告)日: 2011-03-08
- 发明人: Wei Fan , Haixun Wang , Philip S. Yu
- 申请人: Wei Fan , Haixun Wang , Philip S. Yu
- 申请人地址: US NY Armonk
- 专利权人: International Business Machines Corporation
- 当前专利权人: International Business Machines Corporation
- 当前专利权人地址: US NY Armonk
- 代理机构: McGinn IP Law Group, PLLC
- 主分类号: G06F15/18
- IPC分类号: G06F15/18 ; G06N3/00 ; G06N3/12
摘要:
A method (and structure) for processing an inductive learning model for a dataset of examples, includes dividing the dataset of examples into a plurality of subsets of data and generating, using a processor on a computer, a learning model using examples of a first subset of data of the plurality of subsets of data. The learning model being generated for the first subset comprises an initial stage of an evolving aggregate learning model (ensemble model) for an entirety of the dataset, the ensemble model thereby providing an evolving estimated learning model for the entirety of the dataset if all the subsets were to be processed. The generating of the learning model using data from a subset includes calculating a value for at least one parameter that provides an objective indication of an adequacy of a current stage of the ensemble model.
公开/授权文献
- US20100169252A1 SYSTEM AND METHOD FOR SCALABLE COST-SENSITIVE LEARNING 公开/授权日:2010-07-01
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