Decision tree based Neural Networks

Ensembles of neural-networks-based classifiers
decision tree, the neural

(the article support page)

University of Ostrava, 30. dubna 22, 70103 Ostrava, Czech Republic

Authors: Vaclav Kocian, Eva Volna

Article: PDF
Presentation: PDF

Abstract: In the paper we describe an experimental study which was aimed to explore the possibility of using neural network as the base algorithms for so called weak classifiers. We were interested in the possibility of using neural networks in place of commonly used decision trees. Our analysis is based on the idea that it is more efficient to create a number of imperfectly adapted networks small in the topology than one perfectly adapted a sophisticated network. Moreover we assume, that such simple networks will still be more accurate than decision trees. In our experiment neural networks went only through one adaptation cycle. We have generated experimental ensembles of 100 weak classifiers based on five types of neural networks. A total of 3, 240 of such ensembles have been created and tested. We have proposed filtering of input as the new diversity-achieving method. We have tested this method in common with two others methods. The experiment has been conducted over the MNIST database.

Experiment results, used software
Note, that JAVA Runtime Environment version 6 or better

Source: r09728

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But mostly traders are speculating against $$s

2007-11-26 13:29:11 by dylanman

Perhaps the $ selloff is overdone now, who knows. I thought this news bit was interesting. Yen carry traders who have been phreaakked by the pittance of a rate increase by the bank of japan, have been switching over. A good short term call it's proven to be, but I'm skeptical and have a bearish view of the yen.
excerpt from article below:
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