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Relevant Dimension Estimation (RDE) in Feature Spaces

The package provides functions for estimating the relevant dimension of a data set in feature spaces, applications to model selection, graphical illustrations and prediction.

Functions in rdetools

Name Description
rde_tcm Relevant Dimension Estimation (RDE) by Fitting a Two-Component Model (TCM)
sincdata Generate random sinc data
logspace Logarithmically spaced sequence generation
selectmodel Model selection
rbfkernel Calculate RBF kernel matrix
denoiselabels Denoise labels
sinc Calculate sinc values
isregression Estimate from labels whether this is a regression problem
kpr Kernel projection regression
rdetools-package Relevant Dimension Estimation (RDE) in Feature Spaces
distimage Distance image
estnoise Estimate noise level
drawkpc Draw kernel pca coefficients
modelimage Model selection image
rde Relevant Dimension Estimation (RDE)
polykernel Calculate polynomial kernel matrix
rde_loocv Relevant Dimension Estimation (RDE) by Leave-One-Out Cross-Validation (LOO-CV)
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Details

Type Package
Date 2008-09-03
License GPL-2
Packaged 2012-10-29 08:59:34 UTC; ripley
Repository CRAN
Date/Publication 2012-10-29 08:59:34
Contributors Jan Mueller

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