What term describes the measure of decision-making processes in a model applied to specific data examples?

The term that describes the measure of decision-making processes in a model applied to specific data examples is local interpretability. Local interpretability focuses on understanding a model's predictions for individual instances or examples from the dataset. It assesses how the features of a specific input contribute to the model's output, allowing practitioners to and understand the rationale behind the model's decisions for that particular case.

In contrast, global interpretability is concerned with understanding how a model behaves on average across the entire dataset, rather than on individual instances. This would involve examining the overall patterns and relationships identified by the model as a whole. Inductive reasoning refers to a logical process where specific observations lead to generalized conclusions, which isn't specific to model decision processes. Deterministic analysis is a method that assumes systems operate in predictable ways, not directly addressing the complexity of model interpretability. Thus, local interpretability is crucial for providing insights into the decision-making process of a model on a case-by-case basis.