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Reduced-Kernel Weighted Extreme Learning Machine Using Universum Data in Feature Space (RKWELM-UFS) to Handle Binary Class Imbalanced Dataset Classification
2022
Symmetry
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The proposed RKWELM-UFS combines the Universum learning method with a Reduced-Kernelized Weighted Extreme Learning Machine (RKWELM) for the first time to inherit the advantages of both techniques. ...
This paper proposes a novel hybrid framework called Reduced-Kernel Weighted Extreme Learning Machine Using Universum Data in Feature Space (RKWELM-UFS) to handle the classification of binary class-imbalanced ...
The weighted version of RKELM i.e., Reduced-Kernel Weighted Extreme Learning Machine (RKWELM) is proposed in [21] for class imbalance learning. ...
doi:10.3390/sym14020379
fatcat:wanrqfejd5gqldxvvro3e4jibi
Comprehensive Review On Twin Support Vector Machines
[article]
2021
arXiv
pre-print
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
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Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly emerging efficient machine learning techniques which offer promising solutions for classification and regression ...
to solve two SVM kind problems. ...
Recently, Richhariya and Tanveer [118] proposed a reduced universum twin support vector machine for class imbalance learning (RUTWSVM-CIL) with the idea of prior information about the data distribution ...
arXiv:2105.00336v2
fatcat:prxup4sbavfyxpembij6amrnka