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K-means
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#	Item
421	Automatic selection of partitioning schemes for phylogenetic analyses using iterative k-means clustering of site rates Add to Reading List Source URL: digitalcollections.anu.edu.au Language: English - Date: 2015-04-16 13:13:34 Bioinformatics Machine learning Data mining Cluster analysis K-means clustering Multiple sequence alignment K-means++ Neighbor joining Partition Statistics Computational phylogenetics Computational statistics
422	Leveraging Spatio-Temporal Clustering for Participatory Urban Infrastructure Monitoring Add to Reading List Source URL: blog.terracotta.org Language: English - Date: 2014-11-20 13:58:08 Data mining Geostatistics DBSCAN K-means clustering Consensus clustering OPTICS algorithm Statistics Data analysis Cluster analysis
423	Eigenplaces: Segmenting Space through Digital Signatures Add to Reading List Source URL: senseable.mit.edu Language: English - Date: 2010-01-26 13:38:32 Data analysis Multivariate statistics Singular value decomposition Data mining Eigenvalues and eigenvectors Silhouette Wi-Fi K-means clustering Principal component analysis Statistics Algebra Cluster analysis
424	Neural Computation, vol.26, no.1, pp.84–131, Information-Maximization Clustering based on Squared-Loss Mutual Information∗ Add to Reading List Source URL: labs.yahoo.com Language: English - Date: 2014-02-26 18:28:23 Statistical theory Cluster analysis Data mining Geostatistics K-means clustering Kullback–Leibler divergence Mutual information Kernel density estimation Determining the number of clusters in a data set Statistics Multivariate statistics Machine learning
425	ECD Master Thesis Report Textual Data Clustering and Cluster Naming Marian-Andrei RIZOIU Add to Reading List Source URL: www.rizoiu.eu Language: English - Date: 2013-10-18 16:02:59 Multivariate statistics Cluster analysis Geostatistics Machine learning Fuzzy clustering K-means clustering Document clustering Consensus clustering Statistics Data analysis Data mining
426	Cluster Analysis Organize observations into similar groups Outline • Visual clustering • Algorithmic clustering Add to Reading List Source URL: www.ggobi.org Language: English - Date: 2007-10-31 14:32:15 Network analysis K-means clustering Dendrogram Statistics Cluster analysis Hierarchical clustering
427	R Reference Card for Data Mining by Yanchang Zhao, , January 3, 2013 The latest version is available at http://www.RDataMining.com. Click the link also for document R and Data Mining: Examples and Add to Reading List Source URL: ftp.acc.umu.se Language: English - Date: 2013-01-05 06:05:58 Data analysis Consensus clustering K-means clustering Clustering high-dimensional data Oracle Data Mining DBSCAN Hierarchical clustering Data stream clustering Fuzzy clustering Statistics Cluster analysis Multivariate statistics
428	R Reference Card for Data Mining by Yanchang Zhao, , January 3, 2013 The latest version is available at http://www.RDataMining.com. Click the link also for document R and Data Mining: Examples and Add to Reading List Source URL: ftp.yz.yamagata-u.ac.jp Language: English - Date: 2013-01-05 06:05:58 Data analysis Consensus clustering K-means clustering Clustering high-dimensional data Oracle Data Mining DBSCAN Hierarchical clustering Data stream clustering Fuzzy clustering Statistics Cluster analysis Multivariate statistics
429	Canonical k-Means Clustering for Functional Data Thaddeus Tarpey1 and Eva Petkova2 1 Department Mathematics and Statistics, Wright State University, Dayton, Ohio 45435, . 2 Department of Child a Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:19 Multivariate statistics Data mining Geostatistics Hierarchical clustering K-means clustering Principal component analysis Fuzzy clustering Determining the number of clusters in a data set Statistics Cluster analysis Data analysis
430	18 Introduction to Statistical Learning and Pattern Classification Jed Singer and Gabriel Kreiman Add to Reading List Source URL: klab.tch.harvard.edu Language: English - Date: 2013-03-04 08:15:00 Principal component analysis Cluster analysis Unsupervised learning K-means clustering Dimension reduction Linear discriminant analysis Spectral clustering Statistical classification Supervised learning Statistics Machine learning Multivariate statistics

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