Binary Interactive Search Based Facelift Feature Selection Method for Household Classification Data on Smart Electricity Meter Data

M. Suresh, M. Anbarasi
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Abstract

Smart meter data is one among a set of massive data where there are infinite number of features are still inside it which in need of an effective mining approach for extracting from it. However, addressing every features for all problems may not be an effective way for any kind of problem addressing methodology. Hence, based on the need the features to be filtered out to improve the accuracy of the results. In this paper, an effective BIS Algorithm (BISA) has been proposed to address the problem of feature selection for classification of household data. Based on the results, it is evident that the proposed algorithm works efficiently when compared with the other existing algorithms.
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基于二元交互搜索的智能电表户分类数据面部特征选择方法
智能电表数据是海量数据中的一个,其中蕴含着无限多的特征,需要一种有效的挖掘方法来从中提取。然而,对于任何类型的问题处理方法来说,为所有问题处理每个特性可能都不是一种有效的方法。因此,根据需要对特征进行过滤,以提高结果的准确性。本文提出了一种有效的BIS算法(BISA)来解决家庭数据分类中的特征选择问题。实验结果表明,与现有算法相比,本文提出的算法是有效的。
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