• KEEL

  • Referenced in 103 articles [sw06791]
  • various kinds including as regression, classification, unsupervised learning, etc. It includes evolutionary learning algorithms based...
  • fda.usc

  • Referenced in 48 articles [sw14011]
  • atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis of variance...
  • Rmixmod

  • Referenced in 21 articles [sw13560]
  • functions designed to run supervised and unsupervised classification with MIXture MODelling...
  • AutoClass

  • Referenced in 68 articles [sw26092]
  • Bayesian Approach to Classification. We describe a Bayesian approach to the unsupervised discovery of classes ... maximal posterior probability parameters. We rate our classifications with an approximate posterior probability...
  • HMMmix

  • Referenced in 4 articles [sw13500]
  • with mixtures as emission distributions. In unsupervised classification, Hidden Markov Models (HMM) are used...
  • TAHMMAnnot

  • Referenced in 2 articles [sw10508]
  • Unsupervised classification for tiling arrays: chip-chip and transcriptome. Tiling arrays make possible a large ... consider both questions simultaneously as an unsupervised classification problem by modeling the joint distribution...
  • AutoClass@IJM

  • Referenced in 2 articles [sw25643]
  • AutoClass@IJM: a powerful tool for Bayesian classification of heterogeneous data in biology. Recently, several ... applied studies have shown that unsupervised Bayesian classification systems are of particular relevance for biological ... interface to AutoClass, a powerful unsupervised Bayesian classification system developed by the Ames Research Center...
  • RLScore

  • Referenced in 2 articles [sw27570]
  • task and zero-shot learning, and unsupervised classification are included. Matrix algebra based computational short...
  • AntPart

  • Referenced in 1 article [sw01970]
  • AntPart: an algorithm for the unsupervised classification problem using ants...
  • SpaCEM3

  • Referenced in 1 article [sw20896]
  • variety of algorithms for supervised and unsupervised classification of multidimensional and spatially-located data...
  • MDCGen

  • Referenced in 1 article [sw32196]
  • datasets for testing, evaluating, and benchmarking unsupervised classification algorithms. Our proposal fills a gap observed...
  • randomForestSRC

  • Referenced in 10 articles [sw14394]
  • random forests for survival, regression and classification problems based on Ishwaran and Kogalur’s random ... modes. Now extended to include multivariate and unsupervised forests...
  • HistDAWass

  • Referenced in 0 articles [sw18939]
  • between quantile functions. The package contains unsupervised classification techniques, least square regression and tools...
  • Statistics Toolbox

  • Referenced in 18 articles [sw10157]
  • modeling data. You can use regression or classification for predictive modeling, generate random numbers ... squares regression. The toolbox provides supervised and unsupervised machine learning algorithms, including support vector machines...
  • auDeep

  • Referenced in 1 article [sw27628]
  • auDeep is a Python toolkit for deep unsupervised representation learning from acoustic data ... competitive with state-of-the art audio classification...
  • graph2vec

  • Referenced in 5 articles [sw32340]
  • many graph analytics tasks such as graph classification and clustering require representing entire graphs ... graph2vec’s embeddings are learnt in an unsupervised manner and are task agnostic. Hence, they ... downstream task such as graph classification, clustering and even seeding supervised representation learning approaches...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • powerful methodology for solving problems in nonlinear classification, function estimation and density estimation which ... kernel Fisher discriminant analysis and extensions to unsupervised learning, recurrent networks and control are available...
  • FoldingNet

  • Referenced in 3 articles [sw32562]
  • learning tasks on point clouds such as classification and segmentation. In this work, a novel ... deep auto-encoder is proposed to address unsupervised learning challenges on point clouds ... discriminative representation that achieves higher linear SVM classification accuracy than the benchmark. In addition...
  • RolX

  • Referenced in 5 articles [sw32343]
  • making, searching for similar nodes, and node classification. This paper addresses the question: Given ... scalable (linear in the number of edges), unsupervised learning approach for automatically extracting structural roles...
  • subgraph2vec

  • Referenced in 3 articles [sw36496]
  • statistical models for tasks such as graph classification, clustering, link prediction and community detection. subgraph2vec ... learn their latent representations in an unsupervised fashion. We demonstrate that subgraph vectors learnt...