segmentation | R Documentation |
Segmentation of observations based on the grouping of feature effects.
segmentation(fx_vars, data, type, values, max_ngrps = 15)
fx_vars |
List of data frames containing the feature effects. |
data |
Data frame containing the original training data. |
type |
String specifying the type of segmentation. Options are:
|
values |
The values for |
max_ngrps |
Integer specifying the maximum number of groups that each
feature's values/levels are allowed to be grouped into. Only used when
determinining the optimal number of groups via |
Data frame with the segmented data. The grouped features are added to
the original data
and have a trailing underscore in their name.
## Not run:
data('mtpl_be')
features <- setdiff(names(mtpl_be), c('id', 'nclaims', 'expo', 'long', 'lat'))
set.seed(12345)
gbm_fit <- gbm::gbm(as.formula(paste('nclaims ~',
paste(features, collapse = ' + '))),
distribution = 'poisson',
data = mtpl_be,
n.trees = 50,
interaction.depth = 3,
shrinkage = 0.1)
gbm_fun <- function(object, newdata) mean(predict(object, newdata, n.trees = object$n.trees, type = 'response'))
gbm_fit %>% insights(vars = c('ageph', 'bm', 'coverage', 'fuel', 'bm_fuel'),
data = mtpl_be,
interactions = 'user',
pred_fun = gbm_fun) %>%
segmentation(data = mtpl_be,
type = 'ngroups',
values = setNames(c(7, 8, 2, 2, 3), c('ageph', 'bm', 'coverage', 'fuel', 'bm_fuel')))
## End(Not run)
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