In parsnip: A Common API to Modeling and Analysis Functions

r descr_models("logistic_reg", "h2o")

Tuning Parameters

defaults <- 
  tibble::tibble(parsnip = c("penalty", "mixture"),
                 default = c("see below", "see below"))

param <-
logistic_reg() %>% 
  set_engine("h2o") %>% 
  make_parameter_list(defaults)

This model has r nrow(param) tuning parameters:

param$item

Translation from parsnip to the original package

[agua::h2o_train_glm()] for logistic_reg() is a wrapper around [h2o::h2o.glm()]. h2o will automatically picks the link function and distribution family or binomial responses.

logistic_reg() %>% 
  set_engine("h2o") %>% 
  translate()

To use a non-default argument in [h2o::h2o.glm()], pass in as an engine argument to set_engine():

logistic_reg() %>% 
  set_engine("h2o", compute_p_values = TRUE) %>% 
  translate()

Preprocessing requirements

By default, [h2o::h2o.glm()] uses the argument standardize = TRUE to center and scale all numeric columns.

Initializing h2o

Saving fitted model objects

parsnip documentation built on Aug. 18, 2023, 1:07 a.m.