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 ...
Visual Studio Magazine

Kernel Ridge Regression Using C#

KRR is especially useful when there is limited training data, says Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step tutorial. The goal of a machine learning regression problem ...
JSTOR Daily

Sparse Kernel Machine Regression for Ordinal Outcomes

Ordinal outcomes arise frequently in clinical studies when each subject is assigned to a category and the categories have a natural order. Classification rules for ordinal outcomes may be developed ...
JSTOR Daily

Estimation and Comparison of Fractile Graphs Using Kernel Smoothing Techniques

The concept of Fractile Graphical Analysis (FGA) was introduced by Prasanta Chandra Mahalanobis (see Mahalanobis, 1960). It is one of the earliest nonparametric regression techniques to compare two ...