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QLDT+: Efficient Construction of a Quantum Logic Decision Tree

  • The quantum-logic inspired decision tree (QLDT) is based on quantum logic concepts and input values from the unit interval whereas the traditional decision tree is based on Boolean values. The logic behind the QLDT obeys the rules of a Boolean algebra. The QLDT is appropriate for classification problems where for a class decision several input values interact gradually with each other. The QLDT construction for a classification problem with n input attributes requires the computation of 2n minterms. The QLDT+ method, however, uses a heuristic for obtaining a QLDT with much smaller computational complexity. As result, the QLDT+ method can be applied to classification problems with a higher number of input attributes.

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Metadaten
Author: Ingo SchmittORCiDGND
URL:https://dl.acm.org/doi/proceedings/10.1145/3589883
DOI:https://doi.org/10.1145/3589883.3589895
ISBN:978-1-4503-9832-9
Title of the source (English):ICMLT '23: Proceedings of the 2023 8th International Conference on Machine Learning Technologies, SESSION: Session 2 - Data Model Design and Algorithm Analysis
Publisher:Association for Computing Machinery
Place of publication:New York, NY, United States
Document Type:Conference publication peer-reviewed
Language:English
Year of publication:2023
First Page:82
Last Page:88
Way of publication:Open Access
Faculty/Chair:Fakultät 1 MINT - Mathematik, Informatik, Physik, Elektro- und Informationstechnik / FG Datenbank- und Informationssysteme
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