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K-medoids Crazy Firefly Algorithm For Unsupervised Data Clustering

机译:K-MEDOIDS疯狂的萤火虫算法,用于无监督的数据集群

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Data clustering is an unsupervised process in which identical data are collected in groups. A clustering algorithm divides a set of objects into different subsets, these subsets are non-overlapping in nature, and each subset is considered as a cluster. In this paper, a modified clustering approach is developed on integration of k-medoids clustering algorithm with crazy firefly algorithm. The proposed algorithm is experimented on four different datasets. The main aim of the suggested algorithm is to give fast and accurate user specified clustering results from given datasets. Finally, the outcome obtained from the proposed algorithm is compared with both k-medoids clustering algorithm and k-medoids firefly clustering algorithm. The results of the suggested algorithm are better than the k-medoids algorithm and the k-medoids firefly clustering algorithm.
机译:数据群集是一个无监督的过程,其中在组中收集相同的数据。 群集算法将一组对象划分为不同的子集,这些子集本质上是非重叠,并且每个子集被认为是群集。 本文通过疯狂萤火虫算法的k-medoids聚类算法的集成,开发了一种修改的聚类方法。 所提出的算法在四个不同的数据集上进行了实验。 建议算法的主要目的是提供来自给定数据集的快速和准确的用户指定的聚类结果。 最后,将从所提出的算法获得的结果与K-METOIDS聚类算法和K-METOIDS萤火虫聚类算法进行了比较。 建议算法的结果优于K-METOIDS算法和K-METOIDS萤火虫聚类算法。

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