h2o_results: Automated H2O's AutoML Results

In laresbernardo/lares: Analytics & Machine Learning Sidekick

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",
  split = 0.7,
  ignore = NULL,
  quiet = FALSE,
  project = "ML Project",
  seed = 0,
  leaderboard = list(),
  plots = TRUE,
  ...
)

Arguments

h2o_object	H2O Leaderboard (H2OFrame/H2OAutoML) or Model (h2o)
test, train	Dataframe. Must have the same columns
y	Variable or Character. Name of the dependent variable or response.
which	Integer. Which model to select from leaderboard
model_type	Character. Select "Classification" 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.
split	Numeric. Value between 0 and 1 to split as train/test datasets. Value is for training set. Set value to 1 to train with all available data and test with same data (cross-validation will still be used when training). If train_test is set, value will be overwritten with its real split rate.
ignore	Character vector. Columns too ignore
quiet	Boolean. Quiet all messages, warnings, recommendations?
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.
leaderboard	H2O's Leaderboard. Passed when using h2o_selectmodel as it contains plain model and no leader board.
plots	Boolean. Create plots objects?
...	Additional parameters on h2o::h2o.automl

Value

List. Trained model, predicted scores and datasets used, performance metrics, parameters, importance data.frame, seed, and plots when plots=TRUE.

laresbernardo/lares documentation built on Oct. 23, 2024, 12:05 p.m.