RAEDDA_transductive: Robust Eigenvalues Decomposition Discriminant Analysis...

In AndreaCappozzo/raedda: Robust Adaptive Eigenvalue Decomposition Discriminant Analysis

Description

Robust Eigenvalues Decomposition Discriminant Analysis (transductive approach)

Usage

RAEDDA_transductive(Xtrain, cltrain, Xtest, modelscope = NULL, G = NULL,
  alpha_Xtrain = 0, alpha_Xtest = 0.05, tol = 10^-5, iterlim = 1000,
  Aitken = TRUE, ...)

Arguments

Xtrain	A numeric matrix of observations where rows correspond to observations and columns correspond to variables. The group membership of each observation is known - labeled data.
cltrain	A vector (if numeric it will be coerced to factor) with distinct entries representing a classification of the corresponding observations in Xtrain.
Xtest	A numeric matrix of observations where rows correspond to observations and columns correspond to variables. The group membership of each observation may not be known - unlabeled data.
modelscope	A character string indicating the desired models to be tested. With default NULL, all available models are tested. The models available for univariate and multivariate data are described in modelvec
G	A numeric vector indicating the number of expected classes in Xtest. With default NULL, models with G = length(unique(cltrain)): (length(unique(cltrain))+3) are tested.
alpha_Xtrain	The proportion of observations to be trimmed in Xtrain.
alpha_Xtest	The proportion of observations to be trimmed in Xtest.
tol	A non-negative number, with default 10^-5, which is a measure of how strictly convergence is defined.
iterlim	A non-negative integer, with default 1000, which is the desired limit on the maximum number of iterations.
Aitken	A logical value with default TRUE which tests for convergence using Aitken acceleration. If value is set to FALSE, convergence is tested by comparing tol to the change in log-likelihood between two consecutive iterations. For further information on Aitken acceleration, see Aitken
...	Arguments passed to or from other methods

Value

An object of class "raeddat" providing a list of output components for each model in modelscope, with the Best model (according to BIC) first

AndreaCappozzo/raedda documentation built on July 21, 2021, 10:48 a.m.