A granular XGBoost classification algorithm

This paper proposes the first integration of multi-distance granular computing with XGBoost, significantly improving generalization in small-sample scenarios through enriched feature representations. XGBoost (eXtreme Gradient Boosting) is a machine learning algorithm primarily utilized to address cl...

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Bibliographic Details
Published in:	Applied intelligence (Dordrecht, Netherlands) Vol. 55; no. 13; p. 895
Main Authors:	Lan, Biyun, Chen, Yumin, Wu, Keshou
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.08.2025 Springer Nature B.V
Subjects:	Accuracy Algorithms Approximation Artificial Intelligence Classification Computer Science Data processing Data science Datasets Fault diagnosis Information processing Machine learning Machines Manufacturing Mechanical Engineering Processes R&D Representations Research & development Multiple distances Granular computing XGBoost Classification
ISSN:	0924-669X, 1573-7497
Online Access:	Get full text
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