segment {citrus} | R Documentation |
Segment Function
Description
Segments the data by running all steps in the segmentation pipeline, including output table
Usage
segment(
data,
modeltype = c("tree", "k-clusters"),
FUN = NULL,
FUN_preprocess = NULL,
steps = c("preprocess", "model"),
prettify = FALSE,
print_plot = FALSE,
hyperparameters = NULL,
force = FALSE,
verbose = FALSE
)
Arguments
data |
data.frame, the data to segment |
modeltype |
character, the type of model to use to segment choices are: 'tree', 'k-clusters' |
FUN |
function, A user specified function to segment, if the standard methods are not wanting to be used |
FUN_preprocess |
function, A user specified function to preprocess, if the standard methods are not wanting to be used |
steps |
list, names of the steps the user want to run the data on. Options are 'preprocess' and 'model' |
prettify |
logical, TRUE if want cleaned up outputs, FALSE for raw output |
print_plot |
logical, TRUE if want to print the plot |
hyperparameters |
list of hyperparameters to use in the model. |
force |
logical, TRUE to ignore errors in validation step and force model execution. |
verbose |
logical whether information about the segmentation pipeline should be given. |
Value
A list of three objects. A tibble providing high-level segment attributes, a lookup table (data frame) with the id and predicted segment number, and an rpart object defining the model.