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Increasing the interpretability of AI-based credit default models. A rule-extraction proposal based on combining linguistic and unsupervised-fuzzy numeric rules
Increasing the interpretability of AI-based credit default models. A rule-extraction proposal based on combining linguistic and unsupervised-fuzzy numeric rules
Presenters
Associate Professor Juan Manuel Ramon-Jeronimo, Profesor Raquel Florez-Lopez