In parsnip: A Common API to Modeling and Analysis Functions

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r descr_models("logistic_reg", "h2o")

Tuning Parameters

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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:

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param$item

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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.

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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():

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

Preprocessing requirements

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

Initializing h2o

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Saving fitted model objects

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parsnip documentation built on June 8, 2025, 12:10 p.m.