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K-means clustering
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#	Item
671	CPPP/UFMS at ImageCLEF 2014: Robot Vision Task Rodrigo de Carvalho Gomes, Lucas Correia Ribas, Amaury Antˆonio de Castro Junior, Wesley Nunes Gon¸calves Federal University of Mato Grosso do Sul - Ponta Por˜ a Campus Add to Reading List Source URL: ceur-ws.org Language: English - Date: 2014-07-24 09:25:42 Optics Object recognition Pose K-means clustering Caltech 101 Scale-invariant feature transform Computer vision Vision Imaging
672	A classification of European NUTS3 regions Meri Raggi, Sébastien Mary, Fabien Santini, Sergio Gomez Y Paloma 2013 Add to Reading List Source URL: ec.europa.eu Language: English - Date: 2014-04-11 10:38:53 Machine learning Multivariate statistics Psychometrics Latent class model Hierarchical clustering Hierarchical linear modeling Sampling K-means clustering Mixture model Statistics Statistical models Cluster analysis
673	Package ‘vegclust’ July 2, 2014 Type Package Title Fuzzy clustering of vegetation data Version[removed]Date[removed] Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 16:48:46 Cluster analysis Data analysis Data mining Fuzzy clustering K-means clustering Medoid Statistical classification Matrix Wetland Statistics Machine learning Multivariate statistics
674	Efficient Learning on Point Sets Liang Xiong, Barnab´as P´oczos, and Jeff Schneider School of Computer Science Carnegie Mellon University Email: {lxiong,bapoczos,jeff.schneider}@cs.cmu.edu Abstract—Recently several m Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2014-09-10 18:52:46 K-means clustering Support vector machine K-nearest neighbor algorithm Linear classifier Random forest Naive Bayes classifier Pattern recognition Cross-validation Classification rule Statistics Machine learning Statistical classification
675	How to use the vegclust package (ver[removed]Miquel De C´aceres1 1 Centre Tecnol`ogic Forestal de Catalunya. Ctra. St. Lloren¸c de Morunys km 2, 25280, Solsona, Catalonia, Spain Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 16:48:46 K-means clustering K-medoids Fuzzy clustering Statistics Cluster analysis Medoid
676	Package ‘cvxclustr’ July 28, 2014 Maintainer Eric C. Chi Author Eric C. Chi, Kenneth Lange Version 1.1.1 License CC BY-NC-SA 4.0 Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-28 02:28:27 Matrix theory Singular value decomposition Multivariate statistics Data analysis Matrix K-means clustering Eigenvalues and eigenvectors Principal component analysis Mixture model Algebra Mathematics Linear algebra
677	New methods for identifying significant clusters in gene expression data Katherine S. Pollard and Mark J. van der Laan Div. of Biostatistics, Univ. of California, Earl Warren Hall #7360, Berkeley, CA[removed]Key Words: clu Add to Reading List Source URL: stat-www.berkeley.edu Language: English - Date: 2010-03-10 17:30:11 Hierarchical clustering K-means clustering K-medoids Silhouette Gene expression profiling Consensus clustering Gene chip analysis Statistics Cluster analysis Determining the number of clusters in a data set
678	Clustering Learning Objects Collections Using Cluster Ensembles Hanan Ayad and Mohamed Kamel Pattern Analysis and Machine Intelligence Group University of Waterloo, Waterloo, Ontario, Canada [removed] and m Add to Reading List Source URL: www.lornet.ca Language: English - Date: 2006-10-26 11:45:00 K-means clustering Segmentation Complete-linkage clustering Single-linkage clustering Statistics Cluster analysis Consensus clustering
679	Implications of the Recursive Representation Problem for Automatic Concept Identification in On-line Governmental Information ∗ Miles Efron, Gary Marchionini, and Julinang Zhiang School of Information and Library Scien Add to Reading List Source URL: ils.unc.edu Language: English - Date: 2003-11-05 12:03:16 Multivariate statistics Information retrieval Natural language processing Document clustering Hierarchical clustering K-means clustering Document-term matrix Latent semantic indexing Unsupervised learning Statistics Cluster analysis Machine learning
680	11th International Society for Music Information Retrieval Conference (ISMIR[removed]ISLANDS OF GAUSSIANS: THE SELF ORGANIZING MAP AND GAUSSIAN MUSIC SIMILARITY FEATURES Dominik Schnitzer1,2 , Arthur Flexer1 , Gerhard Wid Add to Reading List Source URL: ismir2010.ismir.net Language: English - Date: 2014-01-23 13:05:28 Self-organizing map Cluster analysis Centroid Bregman divergence Kullback–Leibler divergence Jensen–Shannon divergence K-means clustering K-nearest neighbor algorithm Information retrieval Statistics Multivariate statistics Dimension reduction

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