h2o_predict: Prediction wrappers for h2o

In agua: 'tidymodels' Integration with 'h2o'

Prediction wrappers for h2o

Description

Prediction wrappers for fitted models with h2o engine that include data conversion, h2o server cleanup, and so on.

Usage

h2o_predict(object, new_data, ...)

h2o_predict_classification(object, new_data, type = "class", ...)

h2o_predict_regression(object, new_data, type = "numeric", ...)

## S3 method for class ''_H2OAutoML''
predict(object, new_data, id = NULL, ...)

Arguments

object	An object of class model_fit
new_data	A rectangular data object, such as a data frame.
...	Other options passed to h2o::h2o.predict()
type	A single character value or NULL. Possible values are "numeric", "class", "prob", "conf_int", "pred_int", "quantile", "time", "hazard", "survival", or "raw". When NULL, predict() will choose an appropriate value based on the model's mode.
id	Model id in AutoML results.

Details

For AutoML, prediction is based on the best performing model.

Value

For type != "raw", a prediction data frame with the same number of rows as new_data. For type == "raw", return the result of h2o::h2o.predict().

Examples

if (h2o_running()) {
  spec <-
    rand_forest(mtry = 3, trees = 100) %>%
    set_engine("h2o") %>%
    set_mode("regression")

  set.seed(1)
  mod <- fit(spec, mpg ~ ., data = mtcars)
  h2o_predict_regression(mod$fit, new_data = head(mtcars), type = "numeric")

  # using parsnip
  predict(mod, new_data = head(mtcars))
}

agua documentation built on June 7, 2023, 5:07 p.m.