Enhancing Binary Classification by Modeling Uncertain Boundary in Three-Way Decisions.

IEEE Transactions on Knowledge and Data Engineering(2017)

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摘要
Text classification is a process of classifying documents into predefined categories through different classifiers learned from labelled or unlabelled training samples. Many researchers who work on binary text classification attempt to find a more effective way to separate relevant texts from a large data set. However, current text classifiers cannot unambiguously describe the decision boundary be...
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关键词
Support vector machines,Training,Niobium,Data models,Uncertainty,Area measurement,Standards
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