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Foretelling the compressive strength of concrete using twin support vector regression
Characteristic compressive strength is a key and crucial physical attribute of concrete used in various design standards and rules. In this study,...
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Cucumber diseases diagnosis based on multi-class SVM and electronic medical record
Cucumber is one of the most popular vegetable varieties, but leaf disease of cucumber is the key factor restricting the increase of yield. Common...
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ML-SLSTSVM: a new structural least square twin support vector machine for multi-label learning
Multi-label learning (MLL) is a special supervised learning task, where any single instance possibly belongs to several classes simultaneously....
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Functional iterative approach for Universum-based primal twin bounded support vector machine to EEG classification (FUPTBSVM)
Due to the increasing popularity of support vector machine (SVM) and the introduction of Universum, many variants of SVM along with Universum such as...
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Reductive and effective discriminative information-based nonparallel support vector machine
In the paper, to improve the performance of discriminative information-based nonparallel support vector machine (DINPSVM), we propose a novel...
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Nonparallel Support Vector Machine with L2-norm Loss and its DCD-type Solver
The mechanism of L2-norm loss can be explained from the perspective of maximizing margin and minimizing margin variance, which is equivalent to the...
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Parametric non-parallel support vector machines for pattern classification
This paper proposes Parametric non-parallel support vector machines for binary pattern classification. Through an intelligent redesigning of the...
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An efficient regularized K-nearest neighbor structural twin support vector machine
K-nearest neighbor based structural twin support vector machine (KNN-STSVM) performs better than structural twin support vector machine (S-TSVM). It...
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A domain adaptation method by incorporating belief function in twin quarter-sphere SVM
Domain adaptation is a representative problem in transfer learning, which aims to tackle the problem of insufficient labeled data in a target domain...
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Feature Selection Using Sparse Twin Support Vector Machine with Correntropy-Induced Loss
Twin support vector machine (TSVM) has been widely applied to classification problems. But TSVM is sensitive to outliers and is not efficient enough...
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Preliminaries
Figure 2.1 presents the overall procedure of crowdsourced testing. The project manager provides a test task for crowdsourced testing, including the...
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A robust projection twin support vector machine with a generalized correntropy-based loss
The projection twin support vector machine (PTSVM) is a potential tool for classification problem. However the loss function of PTSVM is hinge loss...
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An Intuitionistic Fuzzy Random Vector Functional Link Classifier
Random vector functional link (RVFL) is a widely used powerful model for solving real-life problems in classification and regression. However, the...
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A review of semi-supervised learning for text classification
A huge amount of data is generated daily leading to big data challenges. One of them is related to text mining, especially text classification. To...
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KNN-based least squares twin support vector machine for pattern classification
The least squares twin support vector machine (LSTSVM) generates two non-parallel hyperplanes by directly solving a pair of linear equations as...
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Support Vector Machine Classification
Support vector machine (SVM) has been a popular technique in data analytics. Shi et al. [1] has reported some SVM algorithms. They vary from...
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Pinball loss-based multi-task twin support vector machine and its safe acceleration method
Direct multi-task twin support vector machine (DMTSVM) performs well in handling multiple related tasks. But it is sensitive to noise points due to...
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An efficient multi class Alzheimer detection using hybrid equilibrium optimizer with capsule auto encoder
Alzheimer is an advanced nervous brain disease. In old aged people, Alzheimer is also causing the death. The earlier prediction of Alzheimer’s...
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Node embedding approach for accurate detection of fake reviews: a graph-based machine learning approach with explainable AI
In recent years, online reviews have become increasingly important in promoting various products and services. Unfortunately, writing deceptive...
