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K-means clustering
Results: 985

#	Item
681	Classical clustering methods. Attempt to identify groups of observations that are similar with respect to a certain number of variables. Similarity is “metric”: proximity, given some distance, in a space where observ Add to Reading List Source URL: globin.cse.psu.edu Language: English - Date: 2002-02-14 09:01:05 Bioinformatics Single-linkage clustering Cluster analysis K-means clustering Distance matrix Complete-linkage clustering Statistics Hierarchical clustering Network analysis
682	Journal of Biogeography (J. Biogeogr[removed]ORIGINAL ARTICLE Biogeography of European land Add to Reading List Source URL: www.helsinki.fi Language: English - Date: 2010-03-17 09:49:40 Multivariate statistics Machine learning Cluster analysis Data mining K-means clustering Spatial analysis Computer cluster Grid cell Consensus clustering Statistics Geostatistics Data analysis
683	Cluster analysis for cognitive diagnosis: An application to the 2001 PIRLS reading assessment Chia-Yi Chiu Department of Educational Psychology, Rutgers University, New Brunswick, New Jersey, United States of America Add to Reading List Source URL: www.ierinstitute.org Language: English - Date: 2012-01-04 07:01:18 Multivariate statistics Data mining Geostatistics Complete-linkage clustering Item response theory Single-linkage clustering Hierarchical clustering K-means clustering Attribute Hierarchy Method Statistics Psychometrics Cluster analysis
684	Multiscale Storm Identification and Forecast V Lakshmanan1 , R. Rabin2 , V. DeBrunner3∗ Abstract We describe a recently developed hierarchical K-Means clustering method for weather images. that can be employed to ident Add to Reading List Source URL: www.cimms.ou.edu Language: English - Date: 2003-02-21 13:43:50 Telecommunications engineering Region growing Wireless Watershed Weather radar Market segmentation Synthetic aperture radar Scale-space segmentation Range segmentation Image processing Segmentation Technology
685	Clustering Appearances of Objects Under Varying Illumination Conditions Add to Reading List Source URL: vision.ucsd.edu Language: English - Date: 2003-08-06 19:28:42 Cluster analysis Data mining Geostatistics Spectral clustering Non-negative matrix factorization K-means clustering Segmentation Principal component analysis Consensus clustering Statistics Multivariate statistics Data analysis
686	Microsoft Word - trecvid06-28Feb2007-20h.doc Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2007-03-13 13:55:49 Image processing Unsupervised learning K-means clustering Segmentation Red Digital Cinema Camera Company Statistics Artificial intelligence Learning Video processing Shot transition detection Machine learning
687	Clusterings should not be compared by visual inspection: response to Gagné & Proulx Add to Reading List Source URL: www.helsinki.fi Language: English - Date: 2010-03-17 09:50:35 Machine learning Data mining Geostatistics K-means clustering Hellinger distance Consensus clustering Statistics Cluster analysis Multivariate statistics
688	BJTU TRECVID 2007 Video Search Shikui Wei, Yao Zhao, Zhenfeng Zhu, Nan Liu , Yufeng Zhao, Fang Wang, Xie Lin Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China E-mail: [removed] Add to Reading List Source URL: www-nlpir.nist.gov Language: English - Date: 2007-11-28 11:17:10 Data mining Geostatistics Machine learning K-means clustering Information retrieval Relevance Segmentation Spectral clustering Hierarchical clustering Statistics Multivariate statistics Cluster analysis
689	Cluster Analysis for Cognitive Diagnosis by Chia-Yi Chiu Cluster Analysis for Cognitive Diagnosis: An Application to the 2001 PIRLS Reading Assessment Chia-Yi Chiu, Rutgers, The State University of New Jersey, chia-yi.c Add to Reading List Source URL: www.iea.nl Language: English - Date: 2011-08-10 09:26:30 Machine learning Data mining Geostatistics K-means clustering Hierarchical clustering Complete-linkage clustering Single-linkage clustering Item response theory Expectation–maximization algorithm Statistics Psychometrics Cluster analysis
690	Clustering through Mixture Models General references: Lindsay B.G[removed]), Mixture models: theory, geometry and applications, NFSCBMS Regional Conference Series in Probability and Statistics. McLachlan G.J., Basford K.E. Add to Reading List Source URL: globin.cse.psu.edu Language: English - Date: 2002-02-21 11:52:34 K-means clustering Expectation–maximization algorithm Cluster analysis Principal component analysis Variance Multivariate normal distribution Statistics Data analysis Multivariate statistics

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