In GegznaV/multiROC: Tools for ROC Analyis

opt_def <- knitr::opts_chunk$get()
knitr::opts_chunk$set(collapse = FALSE, comment = "#>")

knitr::opts_chunk$set(fig.width = 6, fig.align = 'center')

Load packages

library(manyROC)

library(manyROC)

Function `cvo_create_folds()`{.r}

# Make some data
dataset_1 <- data.frame(
  ID = rep(1:20, each = 2),
  gr = gl(4, 10, labels = LETTERS[1:4]),
  .row = 1:40
)

# Set parameters
n_folds = 5

# Explore data
str(dataset_1)

# table(dataset_1[,c("gr","ID")])
# summary(dataset_1)

set.seed(1)
cvo_create_folds(block_by = dataset_1$ID, k = n_folds)

When variable names from data frame are provided:

folds_1_a <- cvo_create_folds(
  data = dataset_1,
  stratify_by = "gr",
  block_by = "ID",
  n_folds,
  returnTrain = FALSE
)
# str(folds_1_a)
cvo_test_bs(
  folds_1_a,
  stratify_by = "gr",
  block_by = "ID",
  data = dataset_1
)

When vectors from workspace are provided:

folds_1_b <- cvo_create_folds(
  stratify_by = dataset_1$gr,
  block_by = dataset_1$ID,
  k = n_folds,
  returnTrain = FALSE
)
# str(folds_1_b)
cvo_test_bs(
  folds_1_b,
  stratify_by = "gr",
  block_by = "ID",
  data = dataset_1
)

Not blocked but stratified:

folds_1_c <- cvo_create_folds(
  stratify_by = dataset_1$gr,
  k = n_folds,
  returnTrain = FALSE
)
# str(folds_1_c)
cvo_test_bs(
  folds_1_c, 
  stratify_by = "gr",
  block_by = "ID",
  data = dataset_1
)

Blocked but not stratified:

folds_1_d <- cvo_create_folds(
  block_by = dataset_1$ID,
  k = n_folds,
  returnTrain = FALSE
)
# str(folds_1_d)
cvo_test_bs(
  folds_1_d,
  stratify_by = "gr",
  block_by = "ID",
  dataset_1
)