View source: R/calculate_variable_profile.R
calculate_variable_split | R Documentation |
This function calculate candidate splits for each selected variable. For numerical variables splits are calculated as percentiles (in general uniform quantiles of the length grid_points). For all other variables splits are calculated as unique values.
calculate_variable_split( data, variables = colnames(data), grid_points = 101, variable_splits_type = "quantiles", new_observation = NA ) ## Default S3 method: calculate_variable_split( data, variables = colnames(data), grid_points = 101, variable_splits_type = "quantiles", new_observation = NA )
data |
validation dataset. Is used to determine distribution of observations. |
variables |
names of variables for which splits shall be calculated |
grid_points |
number of points used for response path |
variable_splits_type |
how variable grids shall be calculated? Use "quantiles" (default) for percentiles or "uniform" to get uniform grid of points |
new_observation |
if specified (not |
Note that calculate_variable_split
function is S3 generic.
If you want to work on non standard data sources (like H2O ddf, external databases)
you should overload it.
A named list with splits for selected variables
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