tidy_imp {easyalluvial} | R Documentation |
tidy up dataframe containing model feature importance
Description
returns dataframe with exactly two columns, vars and imp and aggregates dummy encoded variables. Helper function called by all functions that take an imp parameter. Can be called manually if formula for aggregating dummy encoded variables must be modified.
Usage
tidy_imp(imp, df, .f = max, resp_var = NULL)
Arguments
imp |
dataframe or matrix with feature importance information |
df |
dataframe, modeling training data |
.f |
window function, Default: max |
resp_var |
character, prediction variable, can usually be inferred from imp and df. It does not work for all models and needs to be specified in those cases. |
Value
dataframe
- vars
character column with feature names
- imp
numerical column, importance values
Examples
# randomforest
df = mtcars2[, ! names(mtcars2) %in% 'ids' ]
m = randomForest::randomForest( disp ~ ., df)
imp = m$importance
tidy_imp(imp, df)
[Package easyalluvial version 0.3.2 Index]