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  • AS 136
  • Referenced in 275 articles [sw14176]
  • Algorithm AS 136: A K-Means Clustering Algorithm...

  • k-means++
  • Referenced in 119 articles [sw21622]
  • k-means++: The advantages of careful seeding. The k-means method is a widely used ... very appealing in practice. By augmenting k-means with a very simple, randomized seeding technique ... speed and the accuracy of k-means, often quite dramatically...

  • SuLQ
  • Referenced in 121 articles [sw11355]
  • primitive: principal component analysis, k means clustering, the Perceptron Algorithm, the ID3 algorithm, and (apparently...

  • impute
  • Referenced in 99 articles [sw14376]
  • methods such as hierarchical clustering and K-means clustering are not robust to missing data ... Value Decomposition (SVD) based method (SVDimpute), weighted K-nearest neighbors (KNNimpute), and row average...

  • sparcl
  • Referenced in 48 articles [sw16353]
  • Perform sparse hierarchical clustering and sparse k-means clustering. Implements the sparse clustering methods...

  • Vlfeat
  • Referenced in 39 articles [sw13478]
  • feature detectors, feature extractors, (hierarchical) k-means clustering, randomized kd-tree matching, and super-pixelization...

  • J-MEANS
  • Referenced in 67 articles [sw02649]
  • local search heuristic, called J-Means, is proposed for solving the minimum sum of squares ... well-known local search heuristics, K- and H-Means as well as with H-Means...

  • LowRankModels
  • Referenced in 24 articles [sw27002]
  • completion, robust PCA, nonnegative matrix factorization, k-means, and many more. For more information...

  • Pyglrm
  • Referenced in 23 articles [sw27003]
  • completion, robust PCA, nonnegative matrix factorization, k-means, and many more...

  • SPEC Benchmarks
  • Referenced in 23 articles [sw21476]
  • social media NoSQL database transaction and K-Means clustering using map/reduce as two significant...

  • ARPACK
  • Referenced in 783 articles [sw04218]
  • sparse or structured matrices A where structured means that a matrix-vector product ... software is designed to compute a few (k) eigenvalues with user specified features such...

  • Statistics Toolbox
  • Referenced in 18 articles [sw10157]
  • SVMs), boosted and bagged decision trees, k-means and hierarchical clustering, k-nearest neighbor search...

  • KmL
  • Referenced in 12 articles [sw11098]
  • k-means for longitudinal data. KmL, a new package implementing k-means is presented ... real data are presented. Performance of $k$-means on longitudinal data is compared to Proc...

  • GAKREM
  • Referenced in 10 articles [sw02712]
  • clustering algorithm named GAKREM (Genetic Algorithm K-means Logarithmic Regression Expectation Maximization) that combines ... best characteristics of the K-means and EM algorithms but avoids their weaknesses such ... Another novelty is the use of K-means to initially assign data points to clusters ... with the conventional EM algorithm, the K-means algorithm, and the likelihood cross-validation technique...

  • GAPS
  • Referenced in 14 articles [sw02613]
  • modified version, and the well-known K-means algorithm. Sixteen data sets with widely varying...

  • StreamKM++
  • Referenced in 13 articles [sw25552]
  • from the data stream, a weighted k-means algorithm is applied on the coreset...

  • AntClust
  • Referenced in 10 articles [sw01754]
  • partition. We compare AntClust to the K-Means method and to the AntClass algorithm...

  • SymNMF
  • Referenced in 10 articles [sw12668]
  • those by other methods such as K-means. In this paper, we provide further interpretation...

  • fdakma
  • Referenced in 6 articles [sw14401]
  • package fdakma: Functional Data Analysis: K-Mean Alignment. It performs simultaneously clustering and alignment ... unidimensional functional dataset by means of k-mean alignment...

  • cclust
  • Referenced in 9 articles [sw11278]
  • Clustering Indexes. Convex Clustering methods, including K-means algorithm, On-line Update algorithm (Hard Competitive...