Over the past few years, the reconstruction of missing data due to the presence of clouds received an important attention. Applying region-based inpainting strategies or conventional regression ...

Kernel methods and support vector machines (SVMs) serve as cornerstones in modern machine learning, offering robust techniques for both classification and regression tasks. At their core, kernel ...

In this paper, a forecasting method is proposed for economic research, based on multiple kernel support vector regression. In the proposed method, we provide the forecasting framework for economy by ...

Support Vector Machines (SVMs) are indispensable tools in machine learning for tasks like classification and regression. The key to their effectiveness lies in the "kernel trick." In this guide, we ...

I propose adding a Multiple Kernel Learning (MKL) module for kernel optimization in kernel-based methods (such as SVM) to scikit-learn. MKL is a more advanced approach compared to GridSearchCV, ...

The Data Science Lab How to Do Kernel Logistic Regression Using C# Dr. James McCaffrey of Microsoft Research uses code samples, a full C# program and screenshots to detail the ins and outs of kernal ...