Create Autoreport

Creates and (optionally) downloads the autoreport for the experiment.

dai.autoreport(
  model,
  path = getwd(),
  download = TRUE,
  template_path = NULL,
  force = FALSE,
  config_overrides = "",
  mli_key = NULL,
  autoviz_key = NULL,
  individual_rows = NULL,
  placeholders = NULL,
  external_datasets = NULL,
  progress = getOption("dai.progress", TRUE)
)

Arguments

model

DAIModel instance.
path

Destination path - either a directory or a full file path.
download

Whether to directly download the report or not.
template_path

Path to a custom autoreport template, which will be uploaded and used for the rendering.
force

Whether to overwrite the file at dest_path if it already exists.
config_overrides

Raw config.toml file content (UTF8-encoded string) or a list/vector of config variables (optional).
mli_key

MLI instance key (optional).
autoviz_key

Visualization key (optional).
individual_rows

A vector of row indices for rows of interest in the training dataset for which additional information can be shown (ICE, LOCO, KLIME), optional.
placeholders

Additional text to be added to the report as a named list, where the name corresponds to the placeholder in the template, and value is the text to be used instead of the placeholder (optional).
external_datasets

Either a list of DAIFrame objects or a character vector of keys of the datasets to be used for producing additional statistics and plots (optional).
progress

Whether to display a progress bar.

Value

The path of the report.

See also

dai.download_file

Examples

if (FALSE) {
dai.connect(uri = 'http://127.0.0.1:12345', username = 'h2oai', password = 'h2oai')
iris_dai <- as.DAIFrame(iris, progress = FALSE)
# Simple model with minimal parameters
simple_model <- dai.train(training_frame = iris_dai,
                          target_col = 'Species',
                          is_classification = TRUE,
                          is_timeseries = FALSE,
                          time = 1, accuracy = 1, interpretability = 10,
                          progress = FALSE)
# Create and download the report to the current working directory
dai.autoreport(simple_model)
}