TY - GEN A1 - Schmitt, Ingo T1 - QLDT: A Decision Tree Based on Quantum Logic T2 - New Trends in Database and Information Systems. ADBIS 2022 N2 - Besides a good prediction a classifier is to give an explanation how input data is related to the classification result. Decision trees are very popular classifiers and provide a good trade-off between accuracy and explainability for many scenarios. Its split decisions correspond to Boolean conditions on single attributes. In cases when for a class decision several attribute values interact gradually with each other, Boolean-logic-based decision trees are not appropriate. For such cases we propose a quantum-logic inspired decision tree (QLDT) which is based on sums and products on normalized attribute values. In contrast to decision trees based on fuzzy logic a QLDT obeys the rules of the Boolean algebra. KW - Quantum Logic KW - Decission tree KW - Interpretable AI Y1 - 2022 UR - https://opus4.kobv.de/opus4-UBICO/frontdoor/index/index/docId/29481 SN - 978-3-031-15743-1 SN - 978-3-031-15742-4 SP - 299 EP - 308 PB - Springer CY - Switzerland ER -