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DATA REDUCTION METHOD TO ADAPTIVELY SCALE DOWN BANDWIDTH AND COMPUTATION FOR CLASSIFICATION PROBLEMS

机译:用于分类问题的自适应缩减带宽的数据约简方法

摘要

A method is provided for selecting features for classification that trades classification efficiency for computational resources. The method includes ranking a plurality of features of a training set according to how closely they are correlated to their corresponding classifications, receiving sensor data including a plurality of features, and selecting a subset of the features of the sensor data, according to the ranking of the features of the training data such that a computational resource cost of the subset is less than a predefined computational resource maximum and the degree of utility achieved by a classification of the subset of features by a selected classifier is optimized and exceeds a predefined utility minimum.
机译:提供了一种用于选择分类特征的方法,该方法将分类效率与计算资源进行了权衡。该方法包括:根据训练集的多个特征与它们对应的分类的相关程度来对训练集的多个特征进行排名;接收包括多个特征的传感器数据;以及根据对这些特征的排名来选择传感器数据的特征的子集。训练数据的特征,以使子集的计算资源成本小于预定义的计算资源最大值,并且通过选择的分类器对特征子集进行分类所达到的效用程度得到优化,并超过了预定义的效用最小值。

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