HollerithEnergyML: A Prototype of a Machine Learning Energy Consumption Recommender System

Zanger, MichaelSchulz, AlexanderGrodmeier, LukasAgaj, DionSchindler, RafaelWeiss, LukasMöhring, MichaelKlein, MaikeKrupka, DanielWinter, CorneliaGergeleit, MartinMartin, Ludger2024-10-212024-10-212024978-3-88579-746-3https://dl.gi.de/handle/20.500.12116/45106Energy consumption aspects of machine learning classifiers are important for research and practice as well. Due to sparse research in this area, a prototype of a recommender system was developed to provide energy consumption recommendations of different possible classifiers. The prototype is demonstrated as well as discussed and future research points are derived.enAIEnergy ConsumptionMLRecommenderHollerithEnergyML: A Prototype of a Machine Learning Energy Consumption Recommender SystemText/Conference Paper10.18420/inf2024_1321617-5468