big.FE.lasso: Perform LASSO for feature selection and create linear...

In EpidemiumOpenCancer/OpenCancer: Build statistical models to understand cancer causes

Description

Perform LASSO for feature selection and create linear regression using selected features using a big.matrix

Usage

big.FE.lasso(X, yvar = "incidence", labelvar = c("cancer", "age",
  "Country_Transco", "year", "area.x", "area.y"), crossvalidation = T,
  returnplot = T, nfolds = 10, ncores = 1)

Arguments

X	A big.matrix object
yvar	Column name for the explained variable
labelvar	Column name for additional variables
crossvalidation	Should we perform cross-validation
nfolds	Number of folds for cross validation. Ignored if crossvalidation = F. If crossvalidation equals the number of observations, a leave-one-out cross validation is performed
ncores	Number of cores used for computations. If ncores>1, parallel processing is used

Value

Linear model fitted with selected features

EpidemiumOpenCancer/OpenCancer documentation built on May 12, 2019, 7:46 a.m.