VisRuler: Visual analytics for extracting decision rules from bagged and boosted decision trees
A Chatzimparmpas, RM Martins… - Information …, 2023 - journals.sagepub.com
Bagging and boosting are two popular ensemble methods in machine learning (ML) that
produce many individual decision trees. Due to the inherent ensemble characteristic of …
produce many individual decision trees. Due to the inherent ensemble characteristic of …
DeforestVis: Behaviour Analysis of Machine Learning Models with Surrogate Decision Stumps
A Chatzimparmpas, RM Martins… - Computer Graphics …, 2024 - Wiley Online Library
As the complexity of machine learning (ML) models increases and their application in
different (and critical) domains grows, there is a strong demand for more interpretable and …
different (and critical) domains grows, there is a strong demand for more interpretable and …
Does this Explanation Help? Designing Local Model-agnostic Explanation Representations and an Experimental Evaluation Using Eye-tracking Technology
In Explainable Artificial Intelligence (XAI) research, various local model-agnostic methods
have been proposed to explain individual predictions to users in order to increase the …
have been proposed to explain individual predictions to users in order to increase the …
[PDF][PDF] Visual Representation of Explainable Artificial Intelligence Methods: Design and Empirical Studies
MA Meza Martínez - d-nb.info
Explainability is increasingly considered a critical component of artificial intelligence (AI)
systems, especially in high-stake domains where AI systems' decisions can significantly …
systems, especially in high-stake domains where AI systems' decisions can significantly …