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METHOD AND SYSTEM FOR JOINT SELECTION OF A FEATURE SUBSET-CLASSIFIER PAIR FOR A CLASSIFICATION TASK

机译:用于分类任务的特征子分类器对的联合选择的方法和系统

摘要

A method and system for a feature subset-classifier pair for a classification task. The classification task corresponds to automatically classifying data associated with a subject(s) or object(s) of interest into an appropriate class based on a feature subset selected among a plurality of features extracted from the data and a classifier selected from a set of classifier types. The method proposed includes simultaneously determining the feature subset-classifier pair based on a relax-greedy {feature subset, classifier} approach utilizing sub-greedy search process based on a patience function, wherein the feature subset-classifier pair provides an optimal combination for more accurate classification. The automatic joint selection is time efficient solution, effectively speeding up the classification task.
机译:用于分类任务的特征子集-分类器对的方法和系统。分类任务对应于基于从数据中提取的多个特征中选择的特征子集和从一组分类器中选择的分类器,将与感兴趣的一个或多个对象相关联的数据自动分类为适当的类别。类型。所提出的方法包括基于松弛贪婪{特征子集,分类器}方法,同时利用基于耐心函数的子贪婪搜索过程,来确定特征子集-分类器对,其中特征子集-分类器对提供了更多的最优组合。准确的分类。自动关节选择是省时的解决方案,有效地加快了分类任务的速度。

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