lambda_grid | R Documentation |
Create a grid of lambda values that result in a unique grouping.
lambda_grid(
fx_vars,
max_ngrps = 15,
lambda_range = as.vector(outer(seq(1, 10, 0.1), 10^(-7:3)))
)
fx_vars |
List of data frames containing the feature effects. |
max_ngrps |
Integer specifying the maximum number of groups that each feature's values/levels are allowed to be grouped into. |
lambda_range |
Numeric vector of possible values for lambda. |
Tidy data frame (i.e., a "tibble" object) with the lambda grid. The
first column contains the lambda values from lambda_range
which
result in a unique grouping for the features in fx_vars
. There is
one column for each feature containing the optimal number of groups
corresponding to those lambda values.
## 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) %>%
lambda_grid
## End(Not run)
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