Using Diverse Local Optima for Setting Kernel Parameters in Support Vector Regression: Forecasting Emerging Market Credit Spreads
(2024)
Preprint / Working Paper
Anderson, G., & Audzeyeva, A. Using Diverse Local Optima for Setting Kernel Parameters in Support Vector Regression: Forecasting Emerging Market Credit Spreads
We propose a novel approach for determining support vector regression (SVR) kernel parameters in the presence of multiple local optima. In contrast to existing approaches focusing on identifying a single "best" tuning parameter setting, an impractica... Read More about Using Diverse Local Optima for Setting Kernel Parameters in Support Vector Regression: Forecasting Emerging Market Credit Spreads.