varpro_feature_names: Recover original variable names from varpro one-hot encoded...

In ggRandomForests: Visually Exploring Random Forests

Recover original variable names from varpro one-hot encoded feature names

Description

varpro one-hot encodes factor variables, appending a numeric suffix for each level (e.g., sex becomes sex0 and sex1). This function strips those suffixes iteratively until every name in varpro_names can be matched back to a column in dataset.

Usage

varpro_feature_names(varpro_names, dataset)

Arguments

varpro_names	character vector of names as output by varpro (may include one-hot encoded suffixed names such as "sex0", "sex1")
dataset	the original data frame passed to varpro, used to look up valid column names

Value

character vector of unique original variable names (no suffixes)

See Also

gg_partialpro

Examples

## ------------------------------------------------------------------
## Simple case: one continuous variable + one binary factor
## ------------------------------------------------------------------
ds <- data.frame(age = c(25, 30, 45), sex = c("M", "F", "M"))

# varpro one-hot encodes 'sex' into 'sex0' and 'sex1'
varpro_names <- c("age", "sex0", "sex1")
varpro_feature_names(varpro_names, ds)
# Returns: c("age", "sex")

## ------------------------------------------------------------------
## Multi-level factor: three-level 'group' variable
## ------------------------------------------------------------------
ds2 <- data.frame(score = 1:6,
                  group = factor(rep(c("A", "B", "C"), 2)))

# varpro appends 0/1/2 for each level
vn2 <- c("score", "group0", "group1", "group2")
varpro_feature_names(vn2, ds2)
# Returns: c("score", "group")

## ------------------------------------------------------------------
## Already-clean names pass through unchanged
## ------------------------------------------------------------------
ds3 <- data.frame(x = 1:5, y = 1:5)
varpro_feature_names(c("x", "y"), ds3)
# Returns: c("x", "y")

ggRandomForests documentation built on May 2, 2026, 5:06 p.m.