The adaptive-additive algorithm is an approach used primarily in optimization and machine learning settings, particularly in contexts where a model or function is being improved iteratively. While the exact implementation and terminology can vary across different fields, the core idea generally involves two main components: adaptivity and additivity. 1. **Adaptivity**: This refers to the algorithm's ability to adjust or adapt based on the data it encounters during the optimization process.
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