20.500.12556/DKUM-96557 NiaAML AutoML for classification and regression pipelines In this paper we present NiaAML, an AutoML framework that we have developed for creating machine learning pipelines and hyperparameter tuning. The composition of machine learning pipelines is presented as an optimization problem that can be solved using various stochastic, population-based, nature-inspired algorithms. Nature-inspired algorithms are powerful tools for solving real-world optimization problems, especially those that are highly complex, nonlinear, and involve large search spaces where traditional algorithms may struggle. They are applied widely in various fields, including robotics, operations research, and bioinformatics. This paper provides a comprehensive overview of the software architecture, and describes the main tasks of NiaAML, including the automatic composition of classification and regression pipelines. The overview is supported by an practical illustrative example. AutoML classification nature-inspired algorithms optimization klasifikacija algoritmi iz narave optimizacija true false true Elsevier Angleški jezik Slovenski jezik https://www.sciencedirect.com/journal/softwarex © 2024 The Authors Članek v reviji 2026-01-19 13:47:57 2026-01-19 13:47:57 2026-01-20 03:18:46 0000-00-00 00:00:00 2025 0 0 5 str. št. članka 101974 Vol. 29 Feb. 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2024-08-15 2024-11-08 2024-11-20 004.8 219923971 10.1016/j.softx.2024.101974 2352-7110 1-s2.0-S2352711024003443-main.pdf 1-s2.0-S2352711024003443-main.pdf 1 FBCA90EC58A3352C978C54E1254CC2BB 0e91f1f21b7e004df6d9898915f6ae9179dff08a5ea9df541b9c160725784f26 6b05b820-f535-11f0-94a4-00155d580e02 https://dk.um.si/Dokument.php?lang=slv&id=202170 https://www.sciencedirect.com/science/article/pii/S2352711024003443?via%3Dihub#da1 0 70570801-f535-11f0-94a4-00155d580e02 https://dk.um.si/Dokument.php?lang=slv&id=202171 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0