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.

Abstract: This paper presents a study on hierarchical surrogate-assisted evolutionary algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimization ...

Modal regression focuses on estimating the conditional mode—the most probable outcome—given a set of predictors, thereby offering insights that complement classical mean and quantile regression. By ...

ABSTRACT: We present the complete methodology to propose an efficient electrothermal model of the Silicon Carbide (SiC) Metal Oxide Semiconductor Field Effect Transistor (MOSFET), largely used in high ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

In the subject of machine learning, it is essential to comprehend regression algorithms. Ten fundamental regression algorithms are introduced in this tutorial, which serves as the foundation for many ...

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

Abstract: Device independent colour representation is a common operation in order to assure colour consistency throughout the colour measurement and reproduction pipeline, i.e., from input to output ...