easyalluvial: pdp_predictions – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

pdp_predictions

get predictions compatible with the partial dependence plotting method, parallel variant is called by get_pdp_predictions()

get predictions compatible with the partial dependence plotting method, parallel variant is called by get_pdp_predictions()

pdp_predictions(
  df,
  imp,
  m,
  degree = 4,
  bins = 5,
  .f_predict = predict,
  parallel = FALSE
)

`df`	dataframe, training data
`imp`	dataframe, with not more then two columns one of them numeric containing importance measures and one character or factor column containing corresponding variable names as found in training data.
`m`	model object
`degree`	integer, number of top important variables to select. For plotting more than 4 will result in two many flows and the alluvial plot will not be very readable, Default: 4
`bins`	integer, number of bins for numeric variables, increasing this number might result in too many flows, Default: 5
`.f_predict`	corresponding model predict() function. Needs to accept 'm' as the first parameter and use the 'newdata' parameter. Supply a wrapper for predict functions with x-y syntax. For parallel processing the predict method of object classes will not always get imported correctly to the worker environment. We can pass the correct predict method via this parameter for example randomForest:::predict.randomForest. Note that a lot of modeling packages do not export the predict method explicitly and it can only be found using :::.
`parallel`	logical, Default: TRUE