README.md

omlbms - OpenML benchmark suite

This repository helps to create and maintain benchmark suites on OpenML. To use the repository, simply clone it into a local folder and run the following R commands:

devtools::install_github("mlr-org/mlr3oml@oml_run")
devtools::install_github("sebffischer/omlbms")

To work on a benchmark suite, set the option omlbms.path to a new folder, where you will store the files for the benchmark suite

options(omlbms.path = "PATH/TO/YOUR/FOLDER")

To create and curate a benchmark suite using this repository, the a specific folder-structure is suggested. An example is locate in omlbms/inst and its structure is explained below.

example_bms
├── data
│   └── example
│       ├── data.arff
│       ├── data.R
│       ├── description.md
│       └── description.yaml
├── ids
├── suite
│   ├── description.md
│   └── description.yaml
└── tasks
    └── example
        └── description.yaml

data

The data folder contains a subfolder for each dataset that should be uploaded to OpenML. Here the R-Script data.R does the preprocessing of the data and saves the data.arff file in the same folder. The data must be in this format to be able to upload it to OpenML and must be called data.arff The description.md file should contain a proper description of the data as in the example. The description.yaml currently supports.

When this is done, the dataset can be uploaded as follows:

upload_dataset("example")

tasks

To use a task, that is not already on OpenML, create a folder in example_bms/tasks that contains the file description.yaml. This file should contain:

benchmark suite

To initialze the benchmark suite, create the files description.md and description.yaml where description.md contains a proper description of the benchmark suite and the latter contains the alias, the name and the task_ids that should be uploaded. To extend the benchmark suite with a new task, the following call can be made

upload_benchmark_suite("example")

During exploration to easily switch between the public and the test server, set the environment variables OPENMLAPIKEY and OPENMLAPIKEY

To switch to a server (only in the running R session), run either public_server() or test_server(). This also changes the api key.



sebffischer/omlbms documentation built on June 23, 2022, 7:01 p.m.