关于 OWA、机器学习和大数据：综合融资战略优于宇宙

Notes on Intuitionistic Fuzzy Sets Pub Date : 2024-07-01 DOI:10.7546/nifs.2024.30.2.113-120

Panagiotis Chountas, Mustafa Hajmohammed, Ismael Rhemat

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引用次数: 0

摘要

本文通过研究 OWA 下的类发现和类增量学习，为开放世界机器学习提供了一个整体视角。本文详细讨论了当前方法论所面临的挑战、原理和局限性。最后，我们将多个宇宙的 IFS 定义为一种形式主义，用于捕捉大数据中作为增量学习一部分的演化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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On OWA, Machine Learning and Big Data: The case for IFS over universes

This paper provides a holistic view of open-world machine learning by investigating class discovery, and class incremental learning under OWA. The challenges, principles, and limitations of current methodologies are discussed in detail. Finally, we position IFS over multiple universes as a formalism to capture the evolution in Big Data as part of incremental learning.

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Notes on Intuitionistic Fuzzy Sets

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