
tSNE
 Referenced in 95 articles
[sw22300]
 technique called ”tSNE” that visualizes highdimensional data by giving each datapoint a location ... scales. This is particularly important for highdimensional data that lie on several different...

rda
 Referenced in 83 articles
[sw06091]
 Analysis for the classification purpose in high dimensional data...

ROBPCA
 Referenced in 67 articles
[sw11592]
 empirical covariance matrix of the data and hence is highly sensitive to outlying observations ... limited to relatively lowdimensional data. The second approach is based ... projection pursuit and can handle highdimensional data. Here we propose the ROBPCA approach, which...

mboost
 Referenced in 61 articles
[sw07331]
 additive and interaction models to potentially highdimensional data...

GGobi
 Referenced in 43 articles
[sw00345]
 open source visualization program for exploring highdimensional data. It provides highly dynamic and interactive...

ranger
 Referenced in 29 articles
[sw14498]
 Fast Implementation of Random Forests for High Dimensional Data in C++ and R. We introduce ... fast implementation of random forests for high dimensional data. Ensembles of classification, regression and survival...

CoCoA
 Referenced in 631 articles
[sw00143]
 operations on multivaraiate polynomials and on various data related to them (ideals, modules, matrices, rational ... ideal, the ideal of zerodimensional schemes, Poincare’ series and Hilbert functions, factorization of polynomials ... further enhanced by the dedicated highlevel programming language. For convenience, the system offers...

mixOmics
 Referenced in 29 articles
[sw09508]
 integrative techniques and variants to analyse highly dimensional data sets: regularized CCA and sparse ... samples or individuals n. These data may come from high throughput technologies, such as omics...

FAMT
 Referenced in 29 articles
[sw11123]
 FAMT) : simultaneous tests under dependence in highdimensional data. The method proposed in this package ... dependence on the multiple testing procedures for highthroughput data as proposed by Friguet...

LAS
 Referenced in 18 articles
[sw17180]
 Finding large average submatrices in high dimensional data. The search for samplevariable associations ... problem in the exploratory analysis of high dimensional data. Biclustering methods search for samplevariable ... form of distinguished submatrices of the data matrix. (The rows and columns of a submatrix ... discovery of biologically relevant structures in high dimensional data. Software is available...

HDclassif
 Referenced in 15 articles
[sw11114]
 analysis and data clustering methods for high dimensional data, based on the assumption that high...

funHDDC
 Referenced in 19 articles
[sw11130]
 data which adapts the clustering method high dimensional data clustering (HDDC), originally proposed...

huge
 Referenced in 37 articles
[sw08466]
 functions for estimating high dimensional undirected graphs from data. This package implements recent results ... fitting high dimensional semiparametric Gaussian copula models; (3) more functions like datadependent model selection...

WGCNA
 Referenced in 19 articles
[sw07123]
 perform Weighted Correlation Network Analysis on highdimensional data. Includes functions for rudimentary data cleaning...

GAP
 Referenced in 18 articles
[sw26294]
 matrix visualization (MV) and clustering of highdimensional data sets. It provides direct visual perception...

ARfit
 Referenced in 38 articles
[sw00046]
 efficient, in particular when the data are highdimensional. ARfit modules construct approximate confidence intervals...

SOM_PAK
 Referenced in 23 articles
[sw15446]
 codebook vectors into a highdimensional input data space to approximate to its data sets...

uniCox
 Referenced in 14 articles
[sw19131]
 model.. Especially useful for highdimensional data, including microarray data...

gamboostLSS
 Referenced in 13 articles
[sw16111]
 shape and scale (’GAMLSS’) to potentially high dimensional data...

SimBa
 Referenced in 9 articles
[sw28063]
 topological data analysis, a point cloud data P extracted from a metric space is often ... short of scaling well, especially for high dimensional data. In this paper, we investigate ... variety of low and high dimensional data sets. We show that our strategy presents...