An Ontology-Based Concept for Meta AutoML - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2021

An Ontology-Based Concept for Meta AutoML

Bernhard G. Humm
  • Function : Author
  • PersonId : 1105417
Alexander Zender
  • Function : Author
  • PersonId : 1105418

Abstract

Automated machine learning (AutoML) supports ML engineers and data scientists by automating tasks like model selection and hyperparameter optimization. A number of AutoML solutions have been developed, open-source and commercial. We propose a concept called OMA-ML (Ontology-based Meta AutoML) that combines the strengths of existing AutoML solutions by integrating them (meta AutoML).OMA-ML is based on a ML ontology that guides the meta AutoML process. It supports multiple user groups, with and without programming skills. By combining the strengths of AutoML solutions, it supports any number of ML tasks and ML libraries.
Fichier principal
Vignette du fichier
509922_1_En_10_Chapter.pdf (312.22 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03287670 , version 1 (15-07-2021)

Licence

Attribution

Identifiers

Cite

Bernhard G. Humm, Alexander Zender. An Ontology-Based Concept for Meta AutoML. 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2021, Hersonissos, Crete, Greece. pp.117-128, ⟨10.1007/978-3-030-79150-6_10⟩. ⟨hal-03287670⟩
54 View
26 Download

Altmetric

Share

Gmail Facebook X LinkedIn More