sp_manyroc_with_cv_by_variable: Do manyROC analysis with cross-validation for hyperSpec...

Description Usage Arguments Details Value See Also Examples

Description

[!!!] // No description yet //

For reproducible results in parallel computing, set seed with parallel::clusterSetRNGStream(iseed = x)(where x is your seed) (and not with set.seed) as package parallelMap is used for paralellization.

Usage

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## S3 method for class 'hide_it'
print(x, ...)

sp_manyroc_with_cv_by_variable(Spectra, variables_to_analyze,
  k_folds = 3, times = 10, seeds = NULL, kind = NULL)

Arguments

x

an object used to select a method.

...

further arguments passed to or from other methods.

Spectra

hyperSpec object, that contains colum ID for spectra blocking, columns with grouping variables as well as spectroscopic information.

variables_to_analyze

(character)
A character vector with names of grouping variables to use in analysis.

k_folds

(positive integer)
The number of folds in k-fold cross-validation.

times

(positive integer)
The number of repetitions in repeated k-fold cross-validation.

seeds

(NULL | integer)
Either a vector of integers of length times to set seed for each repetition of k-fold cross-validation. For more about seeds see set.seed().

Each seed will be passed to cvo_create_folds.()

kind

character or NULL. If kind is a character string, set R's RNG to the kind desired. Use "default" to return to the R default. See ‘Details’ for the interpretation of NULL.

Details

[!!!] The seeds nust be at least of length 6 and meet other requirements for "L'Ecuyer-CMRG" random number generator.

[!!!] At the moment Seeding section needs revision if it is necessary to use "L'Ecuyer-CMRG" (pseudo)random number generator as set.seed() does not work with parallelMap package. Instead parallel::clusterSetRNGStream(iseed = x) (where x is your seed) should be used with parallelMap to get reproducible results.

Value

A list with results
[!!!] Description needs more specification.

See Also

sp_manyroc_with_cv

Examples

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library(manyROC)

fluorescence$ID  <- 1:nrow(fluorescence)
sp_manyroc_with_cv_by_variable(
        fluorescence[,,500~501],
         c("gr", "class"),
         k_folds = 3,
         times = 2)

GegznaV/manyROC documentation built on Sept. 17, 2018, 2:15 p.m.