Local statistical modeling by cluster-weighted
Methodology
2015-03-13 v3 Computation
Abstract
We investigate statistical properties of Cluster-Weighted Modeling, which is a framework for supervised learning originally developed in order to recreate a digital violin with traditional inputs and realistic sound. The analysis is carried out in comparison with Finite Mixtures of Regression models. Based on some geometrical arguments, we highlight that Cluster-WeightedModeling provides a quite general framework for local statistical modeling. Theoretical results are illustrated on the ground of some numerical simulations.
Cite
@article{arxiv.0911.2634,
title = {Local statistical modeling by cluster-weighted},
author = {Salvatore Ingrassia and Simona C. Minotti and Giorgio Vittadini},
journal= {arXiv preprint arXiv:0911.2634},
year = {2015}
}