rmw_predict_nested_partial_dependencies: Function to calculate partial dependencies from a random...
In skgrange/rmweather: Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data

rmw_predict_nested_partial_dependencies

R Documentation

Function to calculate partial dependencies from a random forest models using a nested tibble.

Function to calculate partial dependencies from a random forest models using a nested tibble.

rmw_predict_nested_partial_dependencies(
  df_nest,
  variables = NA,
  n_cores = NA,
  training_only = TRUE,
  rename = FALSE,
  verbose = FALSE
)

`df_nest`	Nested tibble created by `rmw_model_nested_sets`.
`variables`	Vector of variables to calculate partial dependencies for.
`n_cores`	Number of CPU cores to use for the model calculations.
`training_only`	Should only the training set be used for prediction?
`rename`	Within the `partial_dependencies` nested tibble, should the generic `"variable"` name be renamed to `"variable_model"`. This is useful when `"variable"` has been used as a pollutant identifier.
`verbose`	Should the function give messages?

Nested tibble.

Stuart K. Grange