Predict from stratified models

Usage

# S3 method for class 'tidylearn_stratified'
predict(object, new_data = NULL, ...)

Arguments

object: A tidylearn_stratified model object
new_data: New data for predictions. NULL predicts the training rows from their stored cluster assignments, which works for every clustering method; new rows can be assigned by k-means only.
...: Additional arguments passed to each cluster's model, such as type

Value

A tibble of the columns each cluster's model returns for the requested type – .pred by default, one column per class for type = "prob" – and a .cluster column with cluster assignments. Rows of a single-class cluster are predicted as that class, with probability 1.

Examples

# \donttest{
models <- tl_stratified_models(mtcars, mpg ~ .,
  cluster_method = "kmeans", k = 2, supervised_method = "linear")
preds <- predict(models)
# }