Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...

Click the button above to access the setup page. Follow the on-screen steps to install and activate Geometry Expressions. Geometry Expressions is a powerful symbolic geometry system designed to bridge ...

Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and ...

Abstract: Kernel stochastic configuration networks (KSCNs) belong to the randomized learner model with universal approximation property. However, the original KSCNs model lacks logical reasoning ...

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 ...

Background: Budd-Chiari syndrome (BCS) is a rare global condition with high recurrence rates. Existing prognostic scoring models demonstrate limited predictive efficacy for BCS recurrence. This study ...

Abstract: The method of soft-sensor modeling based on support vector machine is first analysed. Geometry of kernel function is studied from information geometry perspective in view of important ...