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K-means clustering
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#	Item
631	ITCH: Information-Theoretic Cluster Hierarchies Christian B¨ohm1 , Frank Fiedler1 , Annahita Oswald1 , Claudia Plant2 , Bianca Wackersreuther1 , and Peter Wackersreuther1 1 University of Munich, Munich, Germany {boehm,f Add to Reading List Source URL: www.dbs.ifi.lmu.de Language: English - Date: 2010-08-27 08:33:14 Cluster analysis Data mining Geostatistics Hierarchical clustering Information bottleneck method Segmentation OPTICS algorithm K-means clustering Single-linkage clustering Statistics Multivariate statistics Machine learning
632	In Proc. 20th Int. Conf. on Scientific and Statistical Database Management (SSDBM), Hong Kong, China, 2008 A General Framework for Increasing the Robustness of PCA-based Correlation Clustering Algorithms Hans-Peter Krie Add to Reading List Source URL: www.dbs.ifi.lmu.de Language: English - Date: 2008-07-21 10:08:40 Singular value decomposition Machine learning Cluster analysis Principal component analysis Dimension reduction K-means clustering DBSCAN Eigenvalues and eigenvectors Correlation clustering Statistics Multivariate statistics Data analysis
633	In Proc. 20th International Conference on Scientific and Statistical Database Management (SSDBM 2008), Hong Kong, China, 2008, pp[removed]ELKI: A Software System for Evaluation of Subspace Clustering Algorithms Elke Ac Add to Reading List Source URL: www.dbs.ifi.lmu.de Language: English - Date: 2008-07-21 10:09:04 Data mining Machine learning ELKI Hans-Peter Kriegel DBSCAN K-means clustering SUBCLU Weka OPTICS algorithm Statistics Cluster analysis Data analysis
634	Emergence of Object-Selective Features in Unsupervised Feature Learning Adam Coates, Andrej Karpathy, Andrew Y. Ng Computer Science Department Stanford University Add to Reading List Source URL: cs.stanford.edu Language: English - Date: 2012-11-23 20:28:37 Computational statistics Computer vision Pattern recognition Object recognition Supervised learning Invariant Cluster analysis Unsupervised learning K-means clustering Statistics Machine learning Artificial intelligence
635	Vol. 16 no[removed]Pages 707–726 BIOINFORMATICS Genetic network inference: from co-expression Add to Reading List Source URL: arbor.ee.ntu.edu.tw Language: English - Date: 2002-08-06 14:55:43 Cluster analysis Gene regulatory network Gene expression profiling Operon Hierarchical clustering Bioinformatics K-means clustering Regulation of gene expression Consensus clustering Biology Statistics Gene expression
636	A Fast Kernel-based Multilevel Algorithm for Graph Clustering Inderjit Dhillon Yuqiang Guan Add to Reading List Source URL: snap.stanford.edu Language: English - Date: 2011-11-19 02:38:26 Spectral clustering Segmentation K-means clustering Consensus clustering Correlation clustering Statistics Cluster analysis Graph partition
637	A Comparison of Methods for Player Clustering via Behavioral Telemetry Anders Drachen Christian Thurau PLAIT Lab/Game Analytics Add to Reading List Source URL: www.fdg2013.org Language: English - Date: 2013-05-13 10:49:52 Machine learning Formal sciences Linear algebra Non-negative matrix factorization Principal component analysis K-means clustering Cluster analysis Segmentation Pattern recognition Statistics Multivariate statistics Data analysis
638	Middlesex University Research Repository An open access repository of Middlesex University research http://eprints.mdx.ac.uk Afify, Ashraf A. and Dimov, S. S. and Naim, Mohamed and Valeva, Add to Reading List Source URL: eprints.mdx.ac.uk Language: English - Date: 2015-01-06 13:39:38 Machine learning Formal sciences Geostatistics Cluster analysis Data mining K-means clustering Principal component analysis Pattern recognition Consensus clustering Statistics Data analysis Multivariate statistics
639	Hierarchical Framework for Plot De-interlacing of TV Series based on Speakers, Dialogues and Images Philippe Ercolessi, Christine Sénac, Sandrine Mouysset Hervé Bredin Add to Reading List Source URL: herve.niderb.fr Language: English - Date: 2015-01-26 03:58:12 Data mining Geostatistics Machine learning Spectral clustering K-means clustering Segmentation Consensus clustering Statistics Cluster analysis Data analysis
640	scott aaronson, stylometric clustering 17 Stylometric clustering: a comparison of data-driven and syntactic features scott aaronson1 1Computer Science Department, University of California, Berkeley, Berkeley CA[removed] Add to Reading List Source URL: www.scottaaronson.com Language: English - Date: 2006-11-24 03:54:04 Quantitative linguistics Computational linguistics Natural language processing Multivariate statistics Data mining Cluster analysis K-means clustering Parsing Hierarchical clustering Statistics Linguistics Science

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