Invention Grant
- Patent Title: System and method for scalable cost-sensitive learning
- Patent Title (中): 可扩展成本敏感学习的系统和方法
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Application No.: US12690502Application Date: 2010-01-20
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Publication No.: US07904397B2Publication Date: 2011-03-08
- Inventor: Wei Fan , Haixun Wang , Philip S. Yu
- Applicant: Wei Fan , Haixun Wang , Philip S. Yu
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: McGinn IP Law Group, PLLC
- Main IPC: G06F15/18
- IPC: G06F15/18 ; G06N3/00 ; G06N3/12

Abstract:
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.
Public/Granted literature
- US20100169252A1 SYSTEM AND METHOD FOR SCALABLE COST-SENSITIVE LEARNING Public/Granted day:2010-07-01
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