lares (version 4.8.4)

h2o_results: Automated H2O's AutoML Results

Description

This is an auxiliary function to calculate predictions and results when using the h2o_automl() function.

Usage

h2o_results(
  h2o_object,
  test,
  train,
  y = "tag",
  which = 1,
  model_type,
  target = "auto",
  ignored = c(),
  plots = TRUE,
  project = NULL,
  seed = 0,
  quiet = FALSE
)

Arguments

h2o_object

H2O Leaderboard (H2OFrame/H2OAutoML) or Model (h2o)

test, train

Dataframe. Must have the same columns

y

Character. Name of the independent variable

which

Integer. Which model to select from leaderboard

model_type

Character. Select "Classifier" or "Regression"

target

Value. Which is your target positive value? If set to 'auto', the target with largest mean(score) will be selected. Change the value to overwrite. Only used when binary categorical model.

ignored

Character vector. Which columns were ignored?

plots

Boolean. Create plots objects?

project

Character. Your project's name

seed

Integer. Set a seed for reproducibility. AutoML can only guarantee reproducibility if max_models is used because max_time is resource limited.

quiet

Boolean. Quiet messages, warnings, recommendations?

See Also

Other Machine Learning: ROC(), clusterKmeans(), conf_mat(), export_results(), gain_lift(), h2o_automl(), h2o_predict_API(), h2o_predict_MOJO(), h2o_predict_binary(), h2o_predict_model(), h2o_selectmodel(), impute(), iter_seeds(), lasso_vars(), model_metrics(), msplit()