First, an improved K-means clustering algorithm for global earthquake catalogs is proposed. Traditional K-means clustering has several limitations, i.e., the number of clusters needs to be initialized, the initial cluster centers are arbitrarily selected, and there is currently no magnitude parameter...
In our paper for the purpose of initializing the initial centroids of the Improved Hybridized K Means clustering algorithm (IHKMCA) we make use of genetic algorithm, so as to get a more accurate result. The results thus found from the proposed work have better accuracy, more efficient and ...
Clustering with Bregman divergences J. Mach. Learn. Res. (2005) V. Tunali et al. An improved clustering algorithm for text mining: multi-cluster spherical k-means Int. Arab J. Inf. Technol. (2016) S.V. Ault et al. On speech recognition algorithms Int. J. Mach. Learn. Comput. (2018...
In this, we have provided an improved clustering algorithm for segmenting customers using RFM values and compared the performance against the traditional techniques like K-means, single link and complete link.Prabha DhandayudamIlango Krishnamurthi...
Sun, W., Xiang, L., Liu, X., Zhao, D. (2016). An Improved K-medoids Clustering Algorithm Based on a Grid Cell Graph Realized by the P System. In: Zu, Q., Hu, B. (eds) Human Centered Computing. HCC 2016. Lecture Notes in Computer Science(), vol 9567. Springer, Cham. https...
Keywords:clustering;K-meansalgorithm;PSOalgorithm;globaloptimum 0摇引摇言 聚类分析是一种无监督分类技术,按照一定的相 似性标准将数据集进行分类,使得类内的对象尽可能 相似,而不同类之间的对象尽可能相异 [1-2] 。K- means算法 [3] 是基于划分的经典聚类算法,具有容易 理解、实现简单、收敛速度快等许多优...
K-means algorithm is one of the most popular clustering algorithms. However, it is sensitive to initialized partition and the circular dataset. To attack this problem, this paper introduced an improved k-means algorithm based on multiple feature points. The algorithm selects a number of feature ...
This research introduces an improved k-means algonthm which combines hierarchical method with k-means method and the application in the evaluation of air quality levels.In present,evaluation of air quality relies on a tedious index computing based on a formula.A comprehensive analysis on single ...
31 provided an improved DPC with a grid-based high-dimensional clustering algorithm for anomaly detection. Xu et al.32 provided an improved density peaks clustering algorithm based on grid called DPCG to improve the efficiency. Ni et al.3 utilized unsupervised feature selection and density peaks ...
Improve the clustering accuracy of k-means is still an active topic among researchers of the data clustering community from outliers removal and distance metrics perspectives. Herein, a novel modification of the k-means algorithm is proposed based on Tukey’s rule in conjunction with a new ...