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.
IEEE

Advantage and drawback of support vector machine functionality

Abstract: Support Vector Machine(SVM)is one of the most efficient machine learning algorithms, which is mostly used for pattern recognition since its introduction in 1990s. SVMs vast variety of usage, ...
IEEE

Large-Margin Label-Calibrated Support Vector Machines for Positive and Unlabeled Learning

Abstract: Positive and unlabeled learning (PU learning) aims to train a binary classifier based on only PU data. Existing methods usually cast PU learning as a label noise learning problem or a ...
archive

An introduction to support vector machines : and other kernel-based learning methods

Ask the publishers to restore access to 500,000+ books. An icon used to represent a menu that can be toggled by interacting with this icon. A line drawing of the Internet Archive headquarters building ...
TweakTown

MSI Vector GP68HX Gaming Laptop Review

Before we get heavy into the 14th Gen Intel Meteor Lake and Raptor Lake systems, we must first put the wraps on the 13th Gen. To do this, MSI sent over their Vector GP68, a mid-range gaming laptop ...
Frontiers

Levy flight-improved grey wolf optimizer algorithm-based support vector regression model for dam deformation prediction

Considering the strong non-linear time-varying behavior of dam deformation, a novel prediction model, called Levy flight-based grey wolf optimizer optimized support vector regression (LGWO-SVR), is ...
Frontiers

Semi-Supervised Support Vector Machine for Digital Twins Based Brain Image Fusion

The purpose is to explore the feature recognition, diagnosis, and forecasting performances of Semi-Supervised Support Vector Machines (S3VMs) for brain image fusion Digital Twins (DTs). Both unlabeled ...