vboot.multnet: Internal bootstraping validation multinomial glmnet model

Description Usage Arguments

View source: R/parallel_vboot.R

Description

Validate glmnet logistic regression using bootstrap.

Usage

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## S3 method for class 'multnet'
vboot(fit, x, y, s, nfolds = 5, B = 200,
  cv_replicates = 100, n_cores = max(1, parallel::detectCores() - 1))

Arguments

fit

Object from glmnet fit

x

A matrix of the predictors, each row is an observation vector.

y

A vector of response variable. Should be a factor with two levels

s

Value of the penalty parameter "lambda" selected from the original 'cv.glmnet'

nfolds

Number of folds for cross validation as in cv.glmnet

B

Number of bootsrap samples

cv_replicates

Number of replicates for the cross-validation step in 'cv.glmnet'

n_cores

number of cores to use in parallel. Default detectCores()-1


Ancamar/bootValidation documentation built on July 24, 2018, 5:08 p.m.