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Robust support vector quantile regression with truncated pinball loss (RSVQR)
Support vector quantile regression (SVQR) adapts the flexible pinball loss function for empirical risk in regression problems. Furthermore,
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Fuzzy support vector regressions for short-term load forecasting
The accurate short-term point and probabilistic load forecasts are critically important for efficient operation of power systems and electricity...
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Performance of Genocchi wavelet neural networks and least squares support vector regression for solving different kinds of differential equations
In this study, two numerical methods [(a) artificial neural network method with three layers (input layer, hidden layer, output layer) and (b) least...
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An uncertain support vector machine with imprecise observations
Support vector machines have been widely applied in binary classification, which are constructed based on crisp data. However, the data obtained in...
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Numerical simulation of Volterra–Fredholm integral equations using least squares support vector regression
In this paper, a new method based on least squares support vector regression (LS-SVR) is presented as a numerical method for solving linear and...
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Sparse optimization via vector k-norm and DC programming with an application to feature selection for support vector machines
Sparse optimization is about finding minimizers of functions characterized by a number of nonzero components as small as possible, such paradigm...
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Distributionally robust joint chance-constrained support vector machines
In this paper, we investigate the chance-constrained support vector machine (SVM) problem in which the data points are virtually uncertain although...
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A Robust Nonlinear Support Vector Machine Approach for Vehicles Smog Rating Classification
Nowadays all new vehicles are labelled in terms of their emissions thanks to ad hoc legislation. However, from a practical perspective, it is...
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Bilevel hyperparameter optimization for support vector classification: theoretical analysis and a solution method
Support vector classification (SVC) is a classical and well-performed learning method for classification problems. A regularization parameter, which...
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Regression Models
When two or more variables are observed concurrently, it is often of interest to evaluate whether their relationship appears to stay constant over...
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Intuitionistic Fuzzy Laplacian Twin Support Vector Machine for Semi-supervised Classification
In general, data contain noises which come from faulty instruments, flawed measurements or faulty communication. Learning with data in the context of...
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Deep learning theory of distribution regression with CNNs
We establish a deep learning theory for distribution regression with deep convolutional neural networks (DCNNs). Deep learning based on structured...
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Determination of Probability of Failure of Structures Using DBSCAN and Support Vector Machine
Nowadays, the advanced machine learning method, support vector machine (SVM), is used to determine the probability of failure of a system. The aim of...
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Fast hyperbolic wavelet regression meets ANOVA
We use hyperbolic wavelet regression for the fast reconstruction of high-dimensional functions having only low dimensional variable interactions....
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Benign overfitting and adaptive nonparametric regression
We study benign overfitting in the setting of nonparametric regression under mean squared risk, and on the scale of Hölder classes. We construct a...
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Jackknife Model Averaging for Composite Quantile Regression
In this paper, the authors propose a frequentist model averaging method for composite quantile regression with diverging number of parameters....
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Tropical Logistic Regression Model on Space of Phylogenetic Trees
Classification of gene trees is an important task both in the analysis of multi-locus phylogenetic data, and assessment of the convergence of Markov...
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An Approach to Constructing Explicit Estimators in Nonlinear Regression
AbstractWe consider the problem of constructing explicit consistent estimators of finite-dimensional parameters of nonlinear regression models using...
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Credit Scoring Model for Tenants Using Logistic Regression
This study applies logistic regression to compute the tenants’ credit scores in Malaysia based on their characteristics without relying on their...
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MRO Inventory Demand Forecast Using Support Vector Machine – A Case Study
Today’s world is living in the age of digital transformation, the so-called Industry 4.0, in which technological advances have revolutionized the...