Regression is a novel nonparametric methodology that has been developed in the context of statistical learning theory and until …

In this paper we survey the most recent advances in supervised machine learning and highdimensional models for time … predictive ability are brie y reviewed. Finally, we discuss application of machine learning in economics and finance and provide …

Support Vector Machines (SVMs) have become a popular tool for learning with large amounts of high dimensional data … terms of time and memory consumption or because the SVM may be used in an online learning setting. In this paper an approach … for incremental learning with Support Vector Machines is presented, that improves existing approaches. Empirical evidence …

when expectations are formed by adaptive learning within a nonlinear approximation of a model. This novel approach is … applied to a standard New Keynesian model that is estimated using U.S. data. The nonlinear model with adaptive learning … improves model fit compared to the linearized model with and without adaptive learning as well as the nonlinear model with …

Data driven companies effectively use regression machine learning methods for making predictions in many sectors. Cloud …-based Azure Machine Learning Studio (MLS) has a potential of expediting machine learning experiments by offering a convenient and … powerful integrated development environment. The process of evaluating machine learning models in Azure MLS has certain …