Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
Nature

Performance evaluation of different regression models: application in a breast cancer patient data

This paper provides a comprehensive analysis of linear regression models, focusing on addressing multicollinearity challenges in breast cancer patient data. Linear regression methodologies, including ...
Nature

Enhancing accuracy in modelling highly multicollinear data using alternative shrinkage parameters for ridge regression methods

In this study, we introduce three new shrinkage parameters for ridge regression, which dynamically adjust the ridge penalty based on the properties of the data, particularly the multicollinearity ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...