Virtual Reality Visual Data Mining with Nonlinear Discriminant Neural Networks: Application to Leukemia and Alzheimer Gene Expression Data

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TypeArticle
ConferenceProceedings of the International Joint Conference on Neural Networks (IJCNN'05), August 1-4, 2005., Montréal, Québec, Canada
AbstractA hybrid stochastic-deterministic approach for solving NDA problems on very high dimensional biological data is investigated. It is based on networks trained with a combination of simulated annealing and conjugate gradient within a broad scale, high throughput computing data mining environment. High quality networks from the point of view of both discrimination and generalization capabilities are discovered. The NDA mappings generated by these networks, together with unsupervised representations of the data, lead to a deeper understanding of complex high dimensional data like Leukemia and Alzheimer gene expression microarray experiments.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48124
NPARC number5764510
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Record identifier5f1ee200-290e-4821-afa2-2abf9f1951d6
Record created2009-03-29
Record modified2016-05-09
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