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A novel Conceptual Machine Learning Method using Random Conceptual Decomposition

المؤلفAli M.A.
المؤلفJaoua A.
المؤلفAl-Maadeed, SomayaA.
تاريخ الإتاحة2022-05-19T10:23:10Z
تاريخ النشر2020
اسم المنشور2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/ICIoT48696.2020.9089528
معرّف المصادر الموحدhttp://hdl.handle.net/10576/31119
الملخصFormal Concept Analysis (FCA) is emerging in Data Science because of its generality, simplicity, and powerful mathematical foundation. It enabled a uniform data clustering methods into structured space of formal concepts. Several FCA based machine learning (ML) methods gave competitive results compared to classical methods. In another side, ensemble approach proved to be effective by aggregating different basic ML methods. Randomness improved other ML approaches. In this paper, we propose a new conceptual ML method by using random conceptual decomposition. This method integrated and experimented in the context of ensemble learning methods, gave encouraging good results, in general.
راعي المشروعACKNOWLEDGMENT This contribution was made possible by NPRP grant #07-794-1-145 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعCluster analysis
Clustering algorithms
Internet of things
Machine learning
Classical methods
Data clustering methods
Ensemble approaches
Ensemble learning
Formal concept analyses (FCA)
Formal concepts
Machine learning methods
Mathematical foundations
Formal concept analysis
العنوانA novel Conceptual Machine Learning Method using Random Conceptual Decomposition
النوعConference Paper
الصفحات18-22


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