Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
GitHub

TNO Quantum: ML - Classifiers - Support Vector Machine

TNO Quantum provides generic software components aimed at facilitating the development of quantum applications. This package implements a scikit-learn compatible, (quantum) support vector machine.
Scientific Research Publishing

Suykens, J.A.K. and Vandewalle, J. (1999) Least Squares Support Vector Machine Classifiers. Neural Processing Letters, 9, 293-300.

ABSTRACT: Rail corrugation, as a prevalent type of rail damage in heavy railways, induces diseases in the track structure. In order to ensure the safe operation of trains, an improved whale ...
IEEE

Design and Implementation of a Light-Weight Channel Vector Classifier Based on Support Vector Machine for Real-Time 5G Beam Index Detection

Abstract: Machine Learning (ML) is recently considered a key technology for bringing outstanding performance to wireless communications. Conventional research has highlighted the potential of Support ...
GitHub

Support Vector Machine Classifier from scratch

An implementation of a support vector machine classifier written in python for multiclass classification problems. Internally the cvxopt package is used to solve the quadratic programming optimization ...
IEEE

Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifier

Abstract: The system operators usually need to solve large-scale unit commitment problems within limited time frame for computation. This paper provides a pragmatic solution, showing how by learning ...
Scientific Research Publishing

Suykens, J. and Vandewalle, J. (1999) Least Squares Support Vector Machine Classifiers. Neural Processing Letters, 9, 293-300.

ABSTRACT: In this paper, we modify the Bregman APGs (BAPGs) method proposed in (Wang, L, et al.) for solving the support vector machine problem with truncated loss (HTPSVM) given in (Zhu, W, et al.), ...
ascopubs.org

Three Immunomarker Support Vector Machines–Based Prognostic Classifiers for Stage IB Non–Small-Cell Lung Cancer

Phase I Study of Lapatinib in Combination With Chemoradiation in Patients With Locally Advanced Squamous Cell Carcinoma of the Head and Neck We used computer-generated random numbers to study 148 ...