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Fractional Class-Specific Weighted Random Forest Optimization

delete2026-08-08
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OA
AI
N
Nour El Islem Karabadji
A
Abdelghani Lakhdari
A
Ahmed A. Al Nuaim *
A
Ali Algefary
A
Akup Yildirim
A
Ali Assi
M
Mohamed Elati
W
Wajdi Dhifli *
DOI:10.1016/j.inffus.2026.104689delete
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Abstract

Abstract

En 中文
• We propose a class-specific weighted Random Forest framework. • Tree–class weights are optimized via fractional-order gradient descent. • Classical gradient descent is recovered as a special case (α= 1). • Dynamics introduce memory effects to improve optimization. • Extensive validation on 40 UCI datasets shows improved generalization.
Keywords:
Random forest
Classification
Caputo fractional derivatives
Tree weighting
Optimization
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Information Fusion
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Near East University cover
Near East University
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king faisal university
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univ. lille and inserm and chu lille and cnrs
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