LGOct 15, 2024
Machine Learning via rough mereology
arXiv:2410.11579v1h-index: 27
Originality Synthesis-oriented
AI Analysis
This work addresses uncertainty quantification for machine learning and AI applications, but appears incremental as it builds directly on existing rough sets theory.
The authors tackled the problem of uncertainty in machine learning by expanding rough sets to rough mereology, which introduces a measurable degree of uncertainty to these areas.
Rough sets (RS)proved a thriving realm with successes inn many fields of ML and AI. In this note, we expand RS to RM - rough mereology which provides a measurable degree of uncertainty to those areas.