export_results: Export h2o_automl's Results

In laresbernardo/lares: Analytics & Machine Learning Sidekick

Export h2o_automl's Results

Description

Export RDS, TXT, POJO, MOJO and all results from h2o_automl().

Usage

export_results(
  results,
  thresh = 10,
  which = c("txt", "csv", "rds", "binary", "mojo", "plots", "dev", "production"),
  note = NA,
  subdir = NA,
  save = TRUE,
  seed = 0
)

Arguments

results	h2o_automl or h2o model
thresh	Integer. Threshold for selecting binary or regression models: this number is the threshold of unique values we should have in 'tag' (more than: regression; less than: classification)
which	Character vector. Select which file format to export: Possible values: txt, csv, rds, binary, mojo, plots. You might also use dev (txt, csv, rds) or production (binary, mojo) or simply don't use parameter to export everything
note	Character. Add a note to the txt file. Useful when lots of models are trained and saved to remember which one is which one
subdir	Character. In which directory do you wish to save the results?
save	Boolean. Do you wish to save/export results?
seed	Numeric. For reproducible results and random splits.

Value

No return value, called for side effects.

See Also

Other Machine Learning: ROC(), conf_mat(), 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(), model_preprocess(), msplit()

Other Tools: autoline(), bind_files(), bring_api(), chr2num(), db_download(), db_upload(), export_plot(), files_functions(), font_exists(), formatColoured(), formatHTML(), get_credentials(), glued(), grepm(), h2o_selectmodel(), haveInternet(), image_metadata(), importxlsx(), ip_data(), json2vector(), list_cats(), listfiles(), mail_send(), markdown2df(), move_files(), msplit(), myip(), quiet(), read.file(), statusbar(), tic(), try_require(), updateLares(), warnifnot(), what_size()

laresbernardo/lares documentation built on April 19, 2024, 9:40 p.m.