GTM-based data visualisation with incomplete data
Data(s) |
2001
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Resumo |
We analyse how the Generative Topographic Mapping (GTM) can be modified to cope with missing values in the training data. Our approach is based on an Expectation -Maximisation (EM) method which estimates the parameters of the mixture components and at the same time deals with the missing values. We incorporate this algorithm into a hierarchical GTM. We verify the method on a toy data set (using a single GTM) and a realistic data set (using a hierarchical GTM). The results show our algorithm can help to construct informative visualisation plots, even when some of the training points are corrupted with missing values. |
Formato |
application/pdf |
Identificador |
http://eprints.aston.ac.uk/1304/1/NCRG_2001_013.pdf Sun, Yi; Tino, Peter and Nabney, Ian T. (2001). GTM-based data visualisation with incomplete data. Technical Report. Aston University, Birmingham, UK. (Unpublished) |
Publicador |
Aston University |
Relação |
http://eprints.aston.ac.uk/1304/ |
Tipo |
Monograph NonPeerReviewed |