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DATA REDUCTION METHOD TO ADAPTIVELY SCALE DOWN BANDWIDTH AND COMPUTATION FOR CLASSIFICATION PROBLEMS
DATA REDUCTION METHOD TO ADAPTIVELY SCALE DOWN BANDWIDTH AND COMPUTATION FOR CLASSIFICATION PROBLEMS
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机译:用于分类问题的自适应缩减带宽的数据约简方法
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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.
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