format_nfold: Create n-fold cross validation dataset from data frame

View source: R/mm4_format_nfold.R

format_nfoldR Documentation

Create n-fold cross validation dataset from data frame

Description

The format_nfold function takes a data frame with scores, label, and n-fold columns and convert it to a list for evalmod and mmdata.

Usage

format_nfold(nfold_df, score_cols, lab_col, fold_col)

Arguments

nfold_df

A data frame that contains at least one score column, label and fold columns.

score_cols

A character/numeric vector that specifies score columns of nfold_df.

lab_col

A number/string that specifies the label column of nfold_df.

fold_col

A number/string that specifies the fold column of nfold_df.

Value

The format_nfold function returns a list that contains multiple scores and labels.

See Also

evalmod for calculation evaluation measures. mmdata for formatting input data. join_scores and join_labels for formatting scores and labels with multiple datasets.

Examples


##################################################
### Convert dataframe with 2 models and 5-fold datasets
###

## Load test data
data(M2N50F5)
head(M2N50F5)

## Convert with format_nfold
nfold_list1 <- format_nfold(
  nfold_df = M2N50F5, score_cols = c(1, 2),
  lab_col = 3, fold_col = 4
)

## Show the list structure
str(nfold_list1)
str(nfold_list1$scores)
str(nfold_list1$labels)


##################################################
### Speficy a single score column
###

## Convert with format_nfold
nfold_list2 <- format_nfold(
  nfold_df = M2N50F5, score_cols = 1,
  lab_col = 3, fold_col = 4
)

## Show the list structure
str(nfold_list2)
str(nfold_list2$scores)
str(nfold_list2$labels)


##################################################
### Use column names
###

## Convert with format_nfold
nfold_list3 <- format_nfold(
  nfold_df = M2N50F5,
  score_cols = c("score1", "score2"),
  lab_col = "label", fold_col = "fold"
)

## Show the list structure
str(nfold_list3)
str(nfold_list3$scores)
str(nfold_list3$labels)


takayasaito/precrec documentation built on Oct. 19, 2023, 7:28 p.m.