Functional regression models in Hilbert spaces constitute a class of statistical methods that link functional predictors and/or responses via operators defined on infinite-dimensional inner-product ...

Functional linear regression analysis extends classical regression to contexts where predictors, responses or both are functions over continuous domains. In scalar-on-function models, a scalar outcome ...

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.