Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/20738
Title: | On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution |
Authors: | Gallaugher, Michael P.B. |
Advisor: | McNicholas, Paul D. |
Department: | Mathematics and Statistics |
Keywords: | Fractionally Supervised Classification, Clustering, Discriminant Analysis, Mixture Models |
Publication Date: | 2017 |
Abstract: | Recent work on fractionally-supervised classification (FSC), an approach that allows classification to be carried out with a fractional amount of weight given to the unla- belled points, is extended in two important ways. First, and of fundamental impor- tance, the question over how to choose the amount of weight given to the unlabelled points is addressed. Then, the FSC approach is extended to mixtures of multivariate t-distributions. The first extension is essential because it makes FSC more readily applicable to real problems. The second, although less fundamental, demonstrates the efficacy of FSC beyond Gaussian mixture models. |
URI: | http://hdl.handle.net/11375/20738 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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gallaugher_michael_pb_201610_msc.pdf | 532.84 kB | Adobe PDF | View/Open |
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