Nothing
#
# Description of this R script:
# R tests for linear multiple output sparse group lasso routines.
#
# Intended for use with R.
# Copyright (C) 2014 Martin Vincent
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>
#
library(lsgl)
library(methods)
# warnings = errors
options(warn=2)
set.seed(100) # ensures consistency of tests
## Simulate from Y=XB+E, the dimension of Y is N x K, X is N x p, B is p x K
N <- 25 #number of samples
p <- 25 #number of features
K <- 10 #number of groups
B<-matrix(sample(c(rep(1,p*K*0.1),rep(0, p*K-as.integer(p*K*0.1)))),nrow=p,ncol=K)
X<-matrix(rnorm(N*p,1,1),nrow=N,ncol=p)
Y<-X%*%B+matrix(rnorm(N*K,0,1),N,K)
grouping <- rep(LETTERS[1:5],5)
lambda<-lsgl::lambda(X,Y, grouping = grouping, alpha=0, lambda.min=0.1, intercept=FALSE)
fit <-lsgl::fit(X,Y, grouping = grouping, alpha=0, lambda = lambda, intercept=FALSE)
if(min(Err(fit, X)) > 1) stop()
tmp <- which(rowSums(abs(fit$beta[[2]])) != 0)
if(! all((tmp[1]+5*1:4) %in% tmp)) stop()
## Test single fit i.e. K = 1
y <- Y[,1]
lambda<-lsgl::lambda(X,y, grouping = grouping,alpha=0, lambda.min=.5, intercept=FALSE)
fit <-lsgl::fit(X, y, grouping = grouping, alpha=0, lambda = lambda, intercept=FALSE)
res <- predict(fit, X)
tmp <- which(rowSums(abs(fit$beta[[2]])) != 0)
if(! all((tmp[1]+5*1:4) %in% tmp)) stop()
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.