Nothing
r descr_models("naive_Bayes", "klaR")
defaults <- tibble::tibble(parsnip = c("smoothness", "Laplace"), default = c("1.0", "0.0")) param <- naive_Bayes() %>% set_engine("klaR") %>% make_parameter_list(defaults)
This model has r nrow(param)
tuning parameter:
param$item
Note that the engine argument usekernel
is set to TRUE
by default when using the klaR
engine.
r uses_extension("naive_Bayes", "klaR", "classification")
library(discrim) naive_Bayes(smoothness = numeric(0), Laplace = numeric(0)) %>% set_engine("klaR") %>% translate()
The columns for qualitative predictors should always be represented as factors (as opposed to dummy/indicator variables). When the predictors are factors, the underlying code treats them as multinomial data and appropriately computes their conditional distributions.
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