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  • SELP
  • Referenced in 3 articles [sw22586]
  • SELP: semi-supervised evidential label propagation algorithm for graph data clustering. With the increasing size ... applications. In this paper, a new Semi-supervised clustering approach based on an Evidential Label...

  • CECM
  • Referenced in 12 articles [sw06446]
  • semi-supervised) methods have been proposed in the hard or fuzzy clustering frameworks. This approach...

  • DIFFRAC
  • Referenced in 5 articles [sw23902]
  • seen as an alternative to spectral clustering. (3) Prior information on the partition is easily ... performance for semi-supervised learning, for clustering or classification. We present empirical evaluations...

  • ClusPath
  • Referenced in 1 article [sw29979]
  • ClusPath: a temporal-driven clustering to infer typical evolution paths. We propose ClusPath, a novel ... spatio-temporal dissimilarity measure and using semi-supervised clustering techniques. The relations between the evolution...

  • EMCluster
  • Referenced in 6 articles [sw24496]
  • clustering of finite mixture Gaussian distribution with unstructured dispersion in both of unsupervised and semi ... supervised learning...

  • RclusTool
  • Referenced in 0 articles [sw31413]
  • unsupervised clustering, semi-supervised clustering and supervised classification. To assess the processed clusters or classes ... constrain data frame rows (semi-supervised clustering), using Constrained spectral embedding algorithm by Wacquet...

  • DILS
  • Referenced in 2 articles [sw38269]
  • constrained clustering through dual iterative local search. Clustering has always been a powerful tool ... kind of semi-supervised learning: constrained clustering. This technique is a generalization of traditional clustering...

  • GraphDemo
  • Referenced in 1 article [sw10148]
  • data denoising, spectral clustering, label propagation for semi-supervised learning, and so on. However...

  • CLEMM
  • Referenced in 1 article [sw31323]
  • consider parsimonious probabilistic mixture models where the cluster analysis can be improved by projecting ... envelope methods in unsupervised and semi-supervised learning problems. Numerical studies on simulated data ... Gaussian mixture models, K-means and hierarchical clustering algorithms. An R package is available...

  • NEIL
  • Referenced in 2 articles [sw36514]
  • from Internet data. NEIL uses a semi-supervised learning algorithm that jointly discovers common sense ... running for 2.5 months on 200 core cluster (more than 350K CPU hours...

  • LANCELOT
  • Referenced in 310 articles [sw00500]
  • LANCELOT. A Fortran package for large-scale nonlinear...

  • Matlab
  • Referenced in 13702 articles [sw00558]
  • MATLAB® is a high-level language and interactive...

  • mclust
  • Referenced in 315 articles [sw00563]
  • R package mclust: Normal Mixture Modeling for Model...

  • Octave
  • Referenced in 312 articles [sw00646]
  • GNU Octave is a high-level language, primarily...

  • R
  • Referenced in 10196 articles [sw00771]
  • R is a language and environment for statistical...

  • SCIP
  • Referenced in 554 articles [sw01091]
  • SCIP is currently one of the fastest non...

  • GraphBase
  • Referenced in 138 articles [sw01555]
  • The Stanford GraphBase is a freely available collection...

  • WordNet
  • Referenced in 410 articles [sw01777]
  • WordNet® is a large lexical database of English...

  • P-FCM
  • Referenced in 16 articles [sw02421]
  • P-FCM: A proximity-based fuzzy clustering for...

  • L-BFGS
  • Referenced in 852 articles [sw03229]
  • Algorithm 778: L-BFGS-B Fortran subroutines for...