Hybrid Multiobjective Evolutionary Algorithms for Unsupervised QPSO, BBPSO and Fuzzy clustering
Hybrid Multiobjective Evolutionary Algorithms for Unsupervised QPSO, BBPSO and Fuzzy clustering
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DOI：
10.1109/cec45853.2021.9504968
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发表时间：
2021-06
期刊：
影响因子：
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通讯作者：
D. Lai;Yuji Sato
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文献类型：
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作者：
D. Lai;Yuji Sato
虽然多目标进化算法已经有了许多新的发展，但它们在聚类问题中的应用或研究还不多见。本文采用不同的MOEA(SPEA2、IBEA、MOEA/D和MOEA/GLU)、粒子群算法(QPSO和BBPSO)和模糊聚类方法对10种不同的非监督聚类技术在10个公共数据集上进行了实验。应用MOEA的基本原理是增加聚类技术的开发能力，以进一步细化通过模糊聚类或PSO聚类找到的聚类解。其目的是调查不同类型的MOEA应用程序在聚类中的性能，确定MOEA模糊聚类是否优于MOEA PSO变体。总体而言，MOEA/D BBPSO的效果最好。它的性能优于MOEA模糊技术，在具有大量类别的数据集上进行了测试，这些数据集是不平衡的和/或重叠的类别。IBEA模糊聚类的结果最差。研究发现，MOEA/D聚类法的性能优于其他MOEA技术。在这项工作中，我们证明了MOEA/D BBPSO聚类在具有挑战性的数据集上产生了最好的结果。它能够使用MOEA/D深化其开发能力，同时受益于BBPSO在对具有挑战性的数据集进行分类时的探索能力。
While there has been many new developments in multiobjective evolutionary algorithms, they have not been applied or investigated in clustering problems. In this paper, ten different unsupervised clustering techniques applying different MOEA (SPEA2, IBEA, MOEA/D and MOEA/GLU), PSO (QPSO and BBPSO) and Fuzzy approaches are experimented on ten public datasets. The rationale to apply MOEA is to increase the exploitation capabilities of clustering techniques to further refine the cluster solutions found by fuzzy or PSO clustering. The aim is to investigate in the performance of different types of MOEA applications in clustering, determining whether MOEA Fuzzy clustering outperform MOEA PSO variants. Overall, MOEA/D BBPSO was found to produced the best results. It outperformed MOEA Fuzzy techniques, having tested on datasets with high number of classes, that are imbalanced and/or overlapping classes. IBEA Fuzzy clustering was found to produce the worst results. MOEA/D clustering was found to perform better than other MOEA techniques. In this work, we showed that MOEA/D BBPSO clustering produced the best results on challenging datasets. It was able to use MOEA/D to deepen its exploitation capability while benefiting from the exploratory ability of BBPSO when clustering challenging datasets.