read_ml_models: Reads data files for running predictive models.

In jbryer/mldash: Evaluating Machine Learning Models Across Many Datasets

Reads data files for running predictive models.

Description

Information about datasets that can be used in the predictive models are stored in Debian Control Files (dcf). This is the similar to the format used in RMarkdown YAML (i.e. metadata).

Usage

read_ml_models(
  dir = paste0(find.package("mldash"), "/models"),
  pattern = "*.dcf",
  check_for_missing_packages = interactive()
)

Arguments

dir	directory containing the dcf files for the datasets.
pattern	optional regular expression that is used when finding files to read in. It defaults to all dcf files in the dir, but could be a single filename to test a metadata file.
check_for_missing_packages	if TRUE you will be prompted to install missing packages.

Details

• name*The name of the dataset.

• type*Whether this is for a regression or classification model.

• descriptionDescription of the dataset.

• train*The model formula used for the predictive model.

• predict*Any additional information.

• denotes required fields.

Value

a data frame with the following fields:

• nameThe name of the dataset.

• typeWhether this is for a regression or classification model.

• descriptionDescription of the dataset.

• notesAny additional information.

• denotes required fields.

jbryer/mldash documentation built on March 4, 2023, 9:35 p.m.