Conceptual Views on Tree Ensemble Classifiers
| Autor: | Tom Hanika, Johannes Hirth |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Machine Learning Computer Science - Logic in Computer Science Artificial Intelligence (cs.AI) Artificial Intelligence Computer Science - Artificial Intelligence Applied Mathematics 68T30 03G10 68T27 06A15 97R40 Software Machine Learning (cs.LG) Logic in Computer Science (cs.LO) Theoretical Computer Science |
| Popis: | Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are often used to compensate for this disadvantage. Yet, their ability for local explanations, and in particular for global explanations, is limited. In the present work we propose an algebraic method, rooted in lattice theory, for the (global) explanation of tree ensembles. In detail, we introduce two novel conceptual views on tree ensemble classifiers and demonstrate their explanatory capabilities on Random Forests that were trained with standard parameters. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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