Article

Uncertainty and topographic visualisations

2008-01-01

Abstract excerpt

This thesis is a study of low-dimensional visualisation methods for data visualisation under certainty of the input data. It focuses on the two main feed-forward neural network algorithms which are NeuroScale and Generative Topographic Mapping (GTM) by trying to make both algorithms able to accommodate the uncertainty. The two models are shown not to work well under high levels of noise within the data and need to...

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Literature Corpus work: 0a20b6e0-a6f1-5670-8fd9-4ca0018c332b
DOI: 10.48780/publications.aston.ac.uk.00015387

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