Re: A Revolução da Inteligencia Artificial
Enviado: 1/3/2024 17:32
Machine learning algorithms outcomes are more understandable and transparent by XAI techniques, e.g., LIME (local interpretable model-agnostic explanations) (Mathews, 2019), RETAIN (reversed time attention) (Choi et al., 2016), and LRP (layer-wise relevance propagation) (Binder et al., 2016). LIME is a post hoc model in prediction accuracy techniques, which operates as a technique providing explanations and transparency after the decision-making process. A notable advantage of LIME is its model-agnostic nature, enabling its application across various model types. The methodology of LIME entails perturbing or subtly modifying the model's inputs to examine the resulting changes in outputs. This facilitates the identification of inputs that exert the most influence on the outputs, thereby offering valuable insights into the model's decision- making process (Mathews, 2019). RETAIN is an XAI technique focused on healthcare applications to provide transparency, e.g., in heart failure diagnosis (Moreno-Sanchez, 2020).
https://doi.org/10.1016/j.dss.2024.114194