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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Applied intelligence (Dordrecht, Netherlands) Ročník 55; číslo 13; s. 895
Hlavní autori:	Lan, Biyun, Chen, Yumin, Wu, Keshou
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.08.2025 Springer Nature B.V
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!