• 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 11 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 306 articles [sw00500]
  • LANCELOT. A Fortran package for large-scale nonlinear...
  • Matlab

  • Referenced in 13460 articles [sw00558]
  • MATLAB® is a high-level language and interactive...
  • mclust

  • Referenced in 304 articles [sw00563]
  • R package mclust: Normal Mixture Modeling for Model...
  • Octave

  • Referenced in 304 articles [sw00646]
  • GNU Octave is a high-level language, primarily...
  • R

  • Referenced in 9810 articles [sw00771]
  • R is a language and environment for statistical...
  • SCIP

  • Referenced in 536 articles [sw01091]
  • SCIP is currently one of the fastest non...
  • GraphBase

  • Referenced in 135 articles [sw01555]
  • The Stanford GraphBase is a freely available collection...
  • WordNet

  • Referenced in 407 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 805 articles [sw03229]
  • Algorithm 778: L-BFGS-B Fortran subroutines for...