April 2, 2024, 7:43 p.m. | Jaime Gonz\'alez-Gonz\'alez, Francisco de Arriba-P\'erez, Silvia Garc\'ia-M\'endez, Andrea Busto-Casti\~neira, Francisco J. Gonz\'alez-Casta\~no

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.00437v1 Announce Type: cross
Abstract: Automatic legal text classification systems have been proposed in the literature to address knowledge extraction from judgments and detect their aspects. However, most of these systems are black boxes even when their models are interpretable. This may raise concerns about their trustworthiness. Accordingly, this work contributes with a system combining Natural Language Processing (NLP) with Machine Learning (ML) to classify legal texts in an explainable manner. We analyze the features involved in the decision and …

abstract arxiv black boxes classification concerns cs.ai cs.cl cs.lg extraction however knowledge law legal literature raise spanish systems text text classification tree type

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