Herawan, "Big data clustering: a review," in Proc. Int. Conf. on Computational Science and Its Applications, 2014, pp. 707-720.Shirkhorshidi, Ali Seyed, Saeed Aghabozorgi, Teh Ying Wah, and Tutut Herawan. "Big Data clustering: a review." In International Conference on Computational ...
Data clustering: a review. ACM Comput Surv 来自 ResearchGate 喜欢 0 阅读量: 430 作者:AK Jain,MN Murty,PJ Flynn 摘要: The practice of classifying objects according to perceived similarities is the basis for much of science. Organizing data into sensible groupings is one of the most fundamental...
Data clustering: a review. ACM Comp Surveys. 1999;31(3):264–323. Article Google Scholar McQueen JB. Some methods of classification and analysis of multivariate observations. In: Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability, 1967. pp 281–297. Safavian S, ...
Data clustering: a review ACM Comput. Surv. (1999) M.C. Su et al. A modified version of the K-means algorithm with a distance based on cluster symmetry IEEE Trans. Pattern Anal. Mach. Intell. (2001) A.J. Jain, P.J. Flynn (Eds.), Three Dimensional Object Recognition Systems, Else...
Jain, A. K., Murty, M. N. & Flynn, P. J. Data clustering: a review.ACM Comput. Surv.31, 264–323 (1999). Google Scholar Sander, J., Ester, M., Kriegel, H.-P. & Xu, X. Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications.Data Min. Knowl...
Clustering, which has been widely used as a forecasting tool for gene expression data, remains problematic at a very deep level: different initial points of clustering lead to different processes of convergence. However, the setting of initial points is
Data Clustering: Theory Algorithms and Applications by Gan, G., Chaoqun, M. A., and Wu, J It is the review of a book on cluster analysis G Celeux - 《Biometrics》 被引量: 1发表: 2010年 Data Clustering: Theory, Algorithms, and Applications Preface Part I. Clustering, Data and ...
Described by an Objective Function: Finds clusters that minimize or maximize an objective function. How to define the 'goodness' of a clustering. Proximity matrix defines a weighted graph, where the nodes are the points being clustered, and the weighted edges represent the proximities between points...
As a new method, ELM [23] has excellent feature representation capability and easy parameter selection. ELM has been widely used in various machine learning tasks, such as regression and classification [24–30]. Recently, ELM has been extended to clustering. Show abstract A review on extreme le...
[94]. To the best of our knowledge a review paper employing recently developed nature inspired metaheuristics for partitional clustering has not been reported. In 2009 Hruschka et al.[3]have focused on theinitialization procedures, crossover, mutation, fitness evaluation andreselectionassociated with ...