Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer Classification
The use of actual electricity consumption data provided the chance to detect the change of customer class types. This work could be done by using classification techniques. However, there are several challenges in computational techniques. The most important one is to efficiently handle a large numb...
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Format: | Article |
Language: | English |
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MDPI AG
2019-04-01
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Series: | Symmetry |
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Online Access: | https://www.mdpi.com/2073-8994/11/4/498 |
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author | Minghao Piao Yongjun Piao Jong Yun Lee |
author_facet | Minghao Piao Yongjun Piao Jong Yun Lee |
author_sort | Minghao Piao |
collection | DOAJ |
description | The use of actual electricity consumption data provided the chance to detect the change of customer class types. This work could be done by using classification techniques. However, there are several challenges in computational techniques. The most important one is to efficiently handle a large number of dimensions to increase customer classification performance. In this paper, we proposed a symmetrical uncertainty based feature subset generation and ensemble learning method for the electricity customer classification. Redundant and significant feature sets are generated according to symmetrical uncertainty. After that, a classifier ensemble is built based on significant feature sets and the results are combined for the final decision. The results show that the proposed method can efficiently find useful feature subsets and improve classification performance. |
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format | Article |
id | doaj.art-fc5d7a2c4e3041d590b99f68d00b03e2 |
institution | Directory Open Access Journal |
issn | 2073-8994 |
language | English |
last_indexed | 2024-04-13T09:20:36Z |
publishDate | 2019-04-01 |
publisher | MDPI AG |
record_format | Article |
series | Symmetry |
spelling | doaj.art-fc5d7a2c4e3041d590b99f68d00b03e22022-12-22T02:52:37ZengMDPI AGSymmetry2073-89942019-04-0111449810.3390/sym11040498sym11040498Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer ClassificationMinghao Piao0Yongjun Piao1Jong Yun Lee2Department of Computer Science, Chungbuk National University, Cheongju 28644, KoreaThe school of Medicine, Nankai University, Tianjing 300000, ChinaDepartment of Computer Science, Chungbuk National University, Cheongju 28644, KoreaThe use of actual electricity consumption data provided the chance to detect the change of customer class types. This work could be done by using classification techniques. However, there are several challenges in computational techniques. The most important one is to efficiently handle a large number of dimensions to increase customer classification performance. In this paper, we proposed a symmetrical uncertainty based feature subset generation and ensemble learning method for the electricity customer classification. Redundant and significant feature sets are generated according to symmetrical uncertainty. After that, a classifier ensemble is built based on significant feature sets and the results are combined for the final decision. The results show that the proposed method can efficiently find useful feature subsets and improve classification performance.https://www.mdpi.com/2073-8994/11/4/498data miningsymmetrical uncertaintyfeature subsetensemble learningcustomer classification |
spellingShingle | Minghao Piao Yongjun Piao Jong Yun Lee Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer Classification Symmetry data mining symmetrical uncertainty feature subset ensemble learning customer classification |
title | Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer Classification |
title_full | Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer Classification |
title_fullStr | Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer Classification |
title_full_unstemmed | Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer Classification |
title_short | Symmetrical Uncertainty-Based Feature Subset Generation and Ensemble Learning for Electricity Customer Classification |
title_sort | symmetrical uncertainty based feature subset generation and ensemble learning for electricity customer classification |
topic | data mining symmetrical uncertainty feature subset ensemble learning customer classification |
url | https://www.mdpi.com/2073-8994/11/4/498 |
work_keys_str_mv | AT minghaopiao symmetricaluncertaintybasedfeaturesubsetgenerationandensemblelearningforelectricitycustomerclassification AT yongjunpiao symmetricaluncertaintybasedfeaturesubsetgenerationandensemblelearningforelectricitycustomerclassification AT jongyunlee symmetricaluncertaintybasedfeaturesubsetgenerationandensemblelearningforelectricitycustomerclassification |