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METHODS FOR FEATURE SELECTION USING CLASSIFIER ENSEMBLE BASED GENETIC ALGORITHMS

机译:基于分类器遗传算法的特征选择方法

摘要

Methods for performing genetic algorithm-based feature selection are provided herein. In certain embodiments, the methods include steps of applying multiple data splitting patterns to a learning data set to build multiple classifiers to obtain at least one classification resu integrating the at least one classification result from the multiple classifiers to obtain an integrated accuracy resu and outputting the integrated accuracy result to a genetic algorithm as a fitness value for a candidate feature subset, in which genetic algorithm-based feature selection is performed.
机译:本文提供了用于执行基于遗传算法的特征选择的方法。在某些实施例中,所述方法包括以下步骤:将多个数据分裂模式应用于学习数据集以构建多个分类器以获得至少一个分类结果;对来自多个分类器的至少一个分类结果进行积分以获得积分精度结果;将积分的精度结果输出到遗传算法作为候选特征子集的适应度值,在该候选特征子集中执行基于遗传算法的特征选择。

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