use_cvglmnet.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/use_cvglmnet.R
\name{use_cvglmnet}
\alias{use_cvglmnet}
\title{Find best Fit via Cross Validation for glmnet}
\usage{
use_cvglmnet(
  model_matrix,
  response,
  alpha,
  stratify = F,
  family = NULL,
  n_fold = 10,
  parallel = F,
  seed = 12,
  return_both = T,
  standardize = F,
  type_measure = "class",
  ...
)
}
\arguments{
\item{model_matrix}{Model matrix for glmnet made by predictor variables}

\item{response}{Respose vector for glmnet, classification of patients}

\item{alpha}{Value of alpha for fit (elastic net mixing parameter ranging from 0 to 1)}

\item{stratify}{Logical - should folds be stratified by response vector?}

\item{n_fold}{nfold for cv.glmnet() | Default = 90 percent of length(prediction)}

\item{seed}{Integer - Number for set.seed}

\item{return_both}{Logical - Should results of cv.glmnet and glmnet be returned as a list.}

\item{...}{Other arguments passed to glmnet}

\item{predictors}{Character - Set of column names to be used as predictors in regression}

\item{return_plot}{Logical - If set to true, the output is a list of the Regression  results and a correlation plot with AUC plot.}
}
\description{
This function uses glmnet to test which variable of a selected factor is described by other variables in the data set.
}