cross_valid_kfold: cross_valid_kfold

In LewisLabUCSD/RegressionModelPipeline: Pipeline for feature selection, interaction assessment, regression modeling and prediction assessment for 1-1000s of features

Description

k-fold cross validation run to collect predictions for assessment

Usage

cross_valid_kfold(data, formula, resp = all.vars(formula)[1], family,
  K = 10, model = glm, N = 1)

Arguments

data,	a data.frame containing response and observations variables used in the formula.
formula,	relation of response ~ observation to be examined.
resp,	a character vector of the names of dependent/response variables in df
family,	a character string indicating the family associated with the submitted model c('gaussian','binomial','poisson'...)
K,	a numeric variable indicating the number of folds for the k-fold validation
model,	a model associated for testing the variables c(glm,lm)
N,	a numeric value indicating the number of times to run cross-validation

Value

list of cross-validation results: pred_out matrix of predictions (observations x fold), train_out matrix of indicies used for each fold of cross-validation (observations x fold), labels_out matrix of ground truth labels (observations x fold)

LewisLabUCSD/RegressionModelPipeline documentation built on Jan. 11, 2021, 10:33 p.m.