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Tactic: Use Informed Adaptation
Tactic sort:
Awesome Tactic
Type: Architectural Tactic
Category: green-ml-enabled-systems
Title
Use Informed Adaptation
Description
Machine learning models may experience drifts that affect their functionality. In these cases, the models must adapt to the drift. Informed adaptation refers to a method of adapting the ML model only when drift is detected. Therefore, the frequency of adaptation is smaller than in blind, periodic adaptation. Informed adaptation reduces unnecessary adaptations, which consequently saves energy.
Participant
Data Scientist
Related software artifact
Machine Learning Model
Context
Machine Learning
Software feature
< unknown >
Tactic intent
Improve energy efficiency by adapting ML models based on informed drift detection
Target quality attribute
Energy Efficiency
Other related quality attributes
< unknown >
Measured impact
< unknown >
Source
Lorena Poenaru-Olaru, June Sallou, Luis Cruz, Jan S. Rellermeyer, and Arie van Deursen. 2023. Retrain AI Systems Responsibly! Use Sustainable Concept Drift Adaptation Techniques. In 2023 IEEE/ACM 7th International Workshop on Green and Sustainable Software (GREENS). 17–18. (DOI: https://doi.org/10.1109/GREENS59328.2023.00009)Graphical representation
