Title :
Probabilistic NeuroScale for Uncertainty Visualisation
Author :
Sivaraksa, Mingmanas ; Lowe, David
Author_Institution :
Neural Comput. Res. Group, Aston Univ., Birmingham, UK
Abstract :
This paper is a study of low dimensional visualisation methods for data visualisation under uncertainty of the input data. It focuses on NeuroScale, the feed-forward neural networks algorithm by trying to make the algorithm able to accommodate the uncertainty. The standard model is shown not to work well under high levels of noise within the data and need to be modified. The modifications of the model are verified by using synthetic data to show their ability to accommodate the noise.
Keywords :
data visualisation; feedforward neural nets; probability; data visualisation; feed-forward neural networks algorithm; probabilistic neuroscale; uncertainty visualisation; Biological neural networks; Data analysis; Data visualization; Euclidean distance; Feedforward neural networks; Feedforward systems; Level measurement; Neural networks; Noise level; Uncertainty;
Conference_Titel :
Information Visualisation, 2009 13th International Conference
Conference_Location :
Barcelona
Print_ISBN :
978-0-7695-3733-7
DOI :
10.1109/IV.2009.106
