• t-SNE

  • Referenced in 44 articles [sw22300]
  • technique called ”t-SNE” that visualizes high-dimensional data by giving each datapoint a location ... scales. This is particularly important for high-dimensional data that lie on several different...
  • ROBPCA

  • Referenced in 48 articles [sw11592]
  • matrix of the data and hence is highly sensitive to outlying observations. Two robust approaches ... projection pursuit and can handle high-dimensional data. Here we propose the ROBPCA approach, which...
  • mboost

  • Referenced in 48 articles [sw07331]
  • additive and interaction models to potentially high-dimensional data...
  • GGobi

  • Referenced in 40 articles [sw00345]
  • open source visualization program for exploring high-dimensional data. It provides highly dynamic and interactive...
  • FAMT

  • Referenced in 23 articles [sw11123]
  • FAMT) : simultaneous tests under dependence in high-dimensional data. The method proposed in this package...
  • ARfit

  • Referenced in 32 articles [sw00046]
  • efficient, in particular when the data are high-dimensional. ARfit modules construct approximate confidence intervals...
  • SOM_PAK

  • Referenced in 23 articles [sw15446]
  • codebook vectors into a high-dimensional input data space to approximate to its data sets...
  • WGCNA

  • Referenced in 14 articles [sw07123]
  • perform Weighted Correlation Network Analysis on high-dimensional data. Includes functions for rudimentary data cleaning...
  • GAP

  • Referenced in 12 articles [sw26294]
  • matrix visualization (MV) and clustering of high-dimensional data sets. It provides direct visual perception...
  • uniCox

  • Referenced in 12 articles [sw19131]
  • model.. Especially useful for high-dimensional data, including microarray data...
  • HDclassif

  • Referenced in 9 articles [sw11114]
  • data, based on the assumption that high-dimensional data live in different subspaces with...
  • SparseFIS

  • Referenced in 10 articles [sw13736]
  • this paper, we deal with a novel data-driven learning method [sparse fuzzy inference systems ... evaluated, which is based on high-dimensional data from industrial processes and based on benchmark...
  • SpectralCAT

  • Referenced in 7 articles [sw18794]
  • required for most real-world applications data to handle both feature types and their ... called SpectralCAT, for unsupervised clustering of high-dimensional data that contains numerical or nominal ... suggest to automatically transform the high-dimensional input data into categorical values. This is done...
  • WeightedPortTest

  • Referenced in 9 articles [sw12429]
  • Statistical Association: We exploit ideas from high-dimensional data analysis to derive new portmanteau tests...
  • IPSep-CoLa

  • Referenced in 8 articles [sw09789]
  • utility of our technique with sample data from a number of practical applications including gene ... networks, terrorist networks and visualization of high-dimensional data...
  • SPECTRODE

  • Referenced in 6 articles [sw13984]
  • behavior of statistical methods under high-dimensional asymptotics. However, the applicability of the framework ... data is a sample from a multivariate distribution with a given covariance matrix. Under high ... dimensional asymptotics, there is a deterministic map from the distribution of eigenvalues of the population ... broaden the use of RMT in high-dimensional data analysis...
  • bartMachine

  • Referenced in 6 articles [sw10962]
  • detection, model diagnostic plots, incorporation of missing data and the ability to save trees ... handling both large sample sizes and high-dimensional data...
  • hgam

  • Referenced in 73 articles [sw11201]
  • sparsity-smoothness penalty for high-dimensional generalized additive models. The combination of sparsity and smoothness ... well as performance for finite-sample data. We present a computationally efficient algorithm, with provable...
  • varSelRF

  • Referenced in 6 articles [sw08253]
  • highly-correlated variables). Main applications in high-dimensional data (e.g., microarray data, and other genomics...
  • RSPOP

  • Referenced in 6 articles [sw02562]
  • rules and computational complexity arising from high-dimensional data. This decreases the interpretability...