Possibilistic Similarity Measures for Data Science and Machine Learning Applications

Possibilistic Similarity Measures for Data Science and Machine Learning Applications

Measuring similarity is of a great interest in many research areas such as in data sciences, machine learning, pattern recognition, text analysis and information retrieval to name a few. Literature has shown that possibility is an attractive notion in the context of distinguishability assessment and...

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Bibliographic Details
Main Authors: Amal Charfi, Sonda Ammar Bouhamed, Eloi Bosse, Imene Khanfir Kallel, Wassim Bouchaala, Basel Solaiman, Nabil Derbel
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Classification
distance
entropy
learning
measures of specificity
possibility distributions
Online Access:https://ieeexplore.ieee.org/document/9028115/

Internet

https://ieeexplore.ieee.org/document/9028115/

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