Towards Interpreting Multi-Objective Feature Associations

arXiv:2403.00017v1 Announce Type: new
Abstract: Understanding how multiple features are associated and contribute to a specific objective is as important as understanding how each feature contributes to a particular outcome. Interpretability of a single feature in a prediction may be handled in multiple ways; however, in a multi-objective prediction, it is difficult to obtain interpretability of a combination of feature values. To address this issue, we propose an objective specific feature interaction design using multi-labels to find the optimal combination …

abstract arxiv cs.ai cs.lg feature features interpretability multi-objective multiple prediction type understanding