Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/186
Title: Active Learning with Wavelets for Microarray Data
Authors: Vogiatzis, Dimitrios 
Tsapatsoulis, Nicolas 
Keywords: Active learning
Wavelets
Microarray data
Issue Date: 2006
Publisher: Springer Berlin / Heidelberg
Source: Fuzzy Logic and Applications, 2006, pp.252-258
Series/Report no.: Lecture Notes in Computer Science;
Abstract: In Supervised Learning it is assumed that is straightforward to obtained labeled data. However, in reality labeled data can be scarce or expensive to obtain. Active Learning (AL) is a way to deal with the above problem by asking for the labels of the most “informative” data points. We propose a novel AL method based on wavelet analysis, which pertains especially to the large number of dimensions (i.e. examined genes) of microarray experiments. DNA Microarray expression experiments permit the systematic study of the correlation of the expression of thousands of genes. We have applied our method on such data sets with encouraging results. In particular we studied data sets concerning: Small Round Blue Cell Tumours (4 types), Leukemia (2 types) and Lung Cancer (2 types).
Description: 6th International Workshop, WILF 2005, Crema, Italy, September 15-17, 2005, Revised Selected Papers.
URI: http://ktisis.cut.ac.cy/handle/10488/186
ISBN: 9783540325291
ISSN: 10.1007/11676935_31
10.1007/11676935_31
DOI: 10.1007/11676935_31
Rights: © Springer
Appears in Collections:Βιβλία/Books

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