tree_segment.RdRuns decision tree optimisation on the data to segment ids.
tree_segment(data, hyperparameters, verbose = TRUE)
| data | data.frame, the data to segment |
|---|---|
| hyperparameters | list, list of hyperparameters to pass. They include segmentation_variables: a vector or list with variable names that will be used as segmentation variables; dependent_variable: a string with the name of the dependent variable that is used in the clustering; min_segmentation_fraction: integer, the minimum segment size as a proportion of the total data set; number_of_segments: integer, number of leaves you want the decision tree to have. |
| verbose | logical whether information about the segmentation procedure should be given. |
List of 4 objects. The rpart object defining the model, a data frame providing high-level segment attributes, a lookup table (data frame) with the id and predicted segment number, and a list of the hyperparameters used.