192 citations · 426 across the 48 of their papers we have counts for
6 papers · 1 filter
An Apparent Paradox: A Classifier Trained from a Partially Classified Sample May Have Smaller Expected Error Rate Than That If the Sample Were Completely Classified
Daniel Ahfock, Geoffrey J. McLachlan
There has been increasing interest in using semi-supervised learning to form a classifier. As is well known, the (Fisher) information in an unclassified feature with unknown class…
Comment on "Hidden truncation hyperbolic distributions, finite mixtures thereof and their application for clustering" Murray, Browne, and \McNicholas
Geoffrey J. McLachlan, Sharon X. Lee
We comment on the paper of Murray, Browne, and McNicholas (2017), who proposed mixtures of skew distributions, which they termed hidden truncation hyperbolic (HTH). They recently m…
On missing label patterns in semi-supervised learning
Daniel Ahfock, Geoffrey J. McLachlan
We investigate model based classification with partially labelled training data. In many biostatistical applications, labels are manually assigned by experts, who may leave some ob…
Statistical matching of non-Gaussian data
Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan
The statistical matching problem is a data integration problem with structured missing data. The general form involves the analysis of multiple datasets that only have a strict sub…
Approximation by finite mixtures of continuous density functions that vanish at infinity
T Tin Nguyen, Hien D Nguyen, Faicel Chamroukhi +1
Given sufficiently many components, it is often cited that finite mixture models can approximate any other probability density function (pdf) to an arbitrary degree of accuracy. Un…
Mini-batch learning of exponential family finite mixture models
H D Nguyen, F Forbes, G J McLachlan
Mini-batch algorithms have become increasingly popular due to the requirement for solving optimization problems, based on large-scale data sets. Using an existing online expectatio…