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.
Author: | Ingo SchmittORCiDGND |
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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 |