Clustering algorithms: a comparative approach
作者： Dalcimar Casanova , Odemir M. Bruno , Diego R. Amancio , Luciano da F. Costa , Francisco A. Rodrigues
DOI: 10.1371/JOURNAL.PONE.0210236
关键词:
摘要: … We start by revising some of the main approaches to clustering algorithms comparison. Next, we describe the clustering methods considered in the analysis, we also present the R …
arxiv.org
fapesp.br
sci-hub.se 参考文章(106)
Huan Liu, Ehtesham Haque, Lance Parsons, Evaluating Subspace Clustering Algorithms ,(2004)
Charu C. Aggarwal, ChengXiang Zhai, A Survey of Text Clustering Algorithms Mining Text Data. pp. 77- 128 ,(2012) , 10.1007/978-1-4614-3223-4_4
Osama Abu Abbas, Comparisons Between Data Clustering Algorithms. The International Arab Journal of Information Technology. ,vol. 5, pp. 320- 325 ,(2008)
Chii-Ruey Hwang, Simulated annealing: Theory and applications Acta Applicandae Mathematicae. ,vol. 12, pp. 108- 111 ,(1988) , 10.1007/BF00047572
P. Berkhin, A Survey of Clustering Data Mining Techniques Grouping Multidimensional Data. pp. 25- 71 ,(2006) , 10.1007/3-540-28349-8_2
Patrick E. McKight, Julius Najab, Kruskal-Wallis Test Corsini Encyclopedia of Psychology. pp. 1- 1 ,(2010) , 10.1002/9780470479216.CORPSY0491
Graham J. Williams, Zhexue Huang, Mining the Knowledge Mine: The Hot Spots Methodology for Mining Large Real World Databases australian joint conference on artificial intelligence. pp. 340- 348 ,(1997) , 10.1007/3-540-63797-4_87
Data Clustering: Algorithms and Applications Chapman and Hall/CRC. ,(2013) , 10.1201/9781315373515
David E. Goldberg, John H. Holland, Genetic Algorithms and Machine Learning Machine Learning. ,vol. 3, pp. 95- 99 ,(1988) , 10.1023/A:1022602019183
Greg Ridgeway, David Madigan, A Sequential Monte Carlo Method for Bayesian Analysis of Massive Datasets Data Mining and Knowledge Discovery. ,vol. 7, pp. 301- 319 ,(2003) , 10.1023/A:1024084221803