• clusfind

  • Referenced in 447 articles [sw27805]
  • cluster analysis. The programs are described and illustrated in the book ”Finding Groups in Data ... Chapter 2: PAM.FOR (partitions the data set into clusters with a new method using medoids ... Chapter 7: MONA.FOR (divisive hierachical clustering of binary data sets...
  • Neural Network Toolbox

  • Referenced in 175 articles [sw07378]
  • Toolbox for applications such as data fitting, pattern recognition, clustering, time-series prediction, and dynamic ... speed up training and handle large data sets ... distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox...
  • INTLAB

  • Referenced in 439 articles [sw04004]
  • zeros (simple and clusters) interval arithmetic for real and complex data including vectors and matrices...
  • ROCK

  • Referenced in 69 articles [sw37720]
  • robust clustering algorithm for categorical attributes. Clustering, in data mining, is useful ... discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based ... this paper, we study clustering algorithms for data with boolean and categorical attributes. We show ... pair of data points. We develop a robust hierarchical clustering algorithm ROCK that employs links...
  • APCluster

  • Referenced in 107 articles [sw11002]
  • Affinity propagation (AP) is a clustering algorithm that has been introduced by Brendan J. Frey ... exemplars among data points and forms clusters of data points around these exemplars. It operates ... messages between data points until a good set of exemplars and clusters emerges...
  • SAS/STAT

  • Referenced in 419 articles [sw18788]
  • variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster analysis, and nonparametric...
  • DPpackage

  • Referenced in 67 articles [sw10495]
  • data, item response data, longitudinal and clustered data using generalized linear mixed models, and regression...
  • MOCK

  • Referenced in 43 articles [sw04156]
  • benefits of multiple objectives in data clustering In previous work, we have proposed a novel ... approach to data clustering based on the explicit optimization of a partitioning with respect ... automatically determine the number of clusters in a data set. The algorithm has been subject...
  • frailtypack

  • Referenced in 41 articles [sw06070]
  • Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including ... recurrent events with terminal event for clustered data or not. Prediction values are available. Left...
  • Hadoop

  • Referenced in 120 articles [sw08481]
  • distributed processing of large data sets across clusters of computers using simple programming models...
  • COOLCAT

  • Referenced in 29 articles [sw37383]
  • paper we explore the connection between clustering categorical data and entropy: clusters of similar ... COOLCAT, which is capable of efficiently clustering large data sets of records with categorical attributes ... data streams. In contrast with other categorical clustering algorithms published in the past, COOLCAT ... well equipped to deal with clustering of data streams(continuously arriving streams of data point...
  • MIXOR

  • Referenced in 26 articles [sw08990]
  • clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within ... adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed...
  • N-way Toolbox

  • Referenced in 30 articles [sw12996]
  • eemscat for scatter handling of EEM data, clustering for multi-way clustering, CuBatch for batch...
  • impute

  • Referenced in 99 articles [sw14376]
  • Motivation: Gene expression microarray experiments can generate data sets with multiple missing expression values. Unfortunately ... clustering and K-means clustering are not robust to missing data, and may lose effectiveness...
  • funHDDC

  • Referenced in 21 articles [sw11130]
  • work develops a general procedure for clustering functional data which ... adapts the clustering method high dimensional data clustering (HDDC), originally proposed in the multivariate context ... resulting clustering method, called funHDDC, is based on a functional latent mixture model which fits ... functional data in group-specific functional subspaces. By constraining model parameters within and between groups...
  • COSA

  • Referenced in 47 articles [sw22936]
  • procedure is proposed for clustering attribute value data. When used in conjunction with conventional distance...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • Recent developments are in kernel spectral clustering, data visualization and dimensionality reduction, and survival analysis...
  • MULTIMIX

  • Referenced in 34 articles [sw03250]
  • MULTIMIX. The program is designed to cluster multivariate data that have categorical and continuous variables ... example, the program is used to cluster a large medical dataset...
  • HDclassif

  • Referenced in 15 articles [sw11114]
  • Classification and Clustering. Discriminant analysis and data clustering methods for high dimensional data, based...
  • CLUTO

  • Referenced in 18 articles [sw06323]
  • clusters. CLUTO is well-suited for clustering data sets arising in many diverse application areas ... application program can access directly the various clustering and analysis algorithms implemented in CLUTO...