NiaARM: A minimalistic framework for Numerical Association Rule Mining
Author:
Publisher
The Open Journal
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://joss.theoj.org/papers/10.21105/joss.04448.pdf
Reference14 articles.
1. Differential Evolution for Association Rule Mining Using Categorical and Numerical Attributes;Fister;Intelligent Data Engineering and Automated Learning – IDEAL 2018,2018
2. Improved Nature-Inspired Algorithms for Numeric Association Rule Mining;Fister Jr.;Intelligent Computing and Optimization,2021
3. A brief overview of swarm intelligence-based algorithms for numerical association rule mining;Fister Jr.;arXiv:2010.15524 [cs],2020
4. NiaPy: Python microframework for building nature-inspired algorithms;Vrbančič;Journal of Open Source Software,2018
5. Scalable algorithms for association mining;Zaki;IEEE Transactions on Knowledge and Data Engineering,2000
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2. Contribution of low support association rules in understanding the mined knowledge;2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA);2024-02-01
3. Variable-Length Differential Evolution for Numerical and Discrete Association Rule Mining;IEEE Access;2024
4. Evolutionary Selection of a Set of Association Rules Considering Biological Constraints Describing the Prevalent Elements in Bacterial Vaginosis;Mathematical and Computational Applications;2023-06-14
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