no code implementations • 12 Mar 2019 • Michael P. B. Gallaugher, Yang Tang, Paul D. McNicholas
A parametrization of the component scale matrices for the mixture of generalized hyperbolic distributions is proposed by including a penalty term in the likelihood constraining the parameters resulting in a flexible model for high dimensional data and a meaningful interpretation.
1 code implementation • 7 Sep 2018 • Michael P. B. Gallaugher, Paul D. McNicholas
In recent years, data have become increasingly higher dimensional and, therefore, an increased need has arisen for dimension reduction techniques for clustering.
no code implementations • 13 Feb 2018 • Michael P. B. Gallaugher, Paul D. McNicholas
A mixture of first-order continuous time Markov models is introduced for unsupervised and semi-supervised learning of clickstream data.
1 code implementation • 22 Dec 2017 • Michael P. B. Gallaugher, Paul D. McNicholas
This is perhaps especially true for clustering (unsupervised classification) as well as semi-supervised and supervised classification.