Author:
Zender Alexander,Humm Bernhard G.
Abstract
Automated machine learning (AutoML) supports ML engineers and data scientist by automating single tasks like model selection and hyperparameter optimization, automatically generating entire ML pipelines. This article presents a survey of 20 state-of-the-art AutoML solutions, open source and commercial. There is a wide range of functionalities, targeted user groups, support for ML libraries, and degrees of maturity. Depending on the AutoML solution, a user may be locked into one specific ML library technology or one product ecosystem. Additionally, the user might require some expertise in data science and programming for using the AutoML solution. We propose a concept called OMA-ML (Ontology-based Meta AutoML) that combines the features of existing AutoML solutions by integrating them (Meta AutoML). OMA-ML can incorporate any AutoML solution allowing various user groups to generate ML pipelines with the ML library of choice. An ontology is the information backbone of OMA-ML. OMA-ML is being implemented as an open source solution with currently third-party 7 AutoML solutions being integrated.
Subject
Artificial Intelligence,Computational Theory and Mathematics,Computer Science Applications,Theoretical Computer Science,Software
Reference56 articles.
1. Russell SJ, Norvig P. Artificial intelligence: A modern approach. 3rd ed. Prentice Hall Series in Artificial Intelligence. Upper Saddle River: Pearson; 2016.
2. A method for balancing a multi-labeled biomedical dataset;Mukhin;Integrated Computer-Aided Engineering,2022
3. Conditional StyleGAN modelling and analysis for a machining digital twin;Zotov;Integrated Computer-Aided Engineering,2021
4. A three-step model for the detection of stable grasp points with machine learning;Schwan;Integrated Computer-Aided Engineering,2021
5. An ensemble deep learning method with optimized weights for drone-based water rescue and surveillance;Ga̧sienica-Józkowy;Integrated Computer-Aided Engineering,2021
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献