| Issue |
MATEC Web Conf.
Volume 79, 2016
VII Scientific Conference with International Participation “Information-Measuring Equipment and Technologies” (IME&T 2016)
|
|
|---|---|---|
| Article Number | 01075 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/matecconf/20167901075 | |
| Published online | 11 October 2016 | |
Design of Neuro-Fuzzy Decision Trees
National Research Tomsk State University, 634050, Tomsk, Russia
* Corresponding author: tanusha-atv@mail.ru
In order to improve accuracy of fuzzy decision trees classification we propose a procedure of parameters adaptation by means of neural network training. In the direct cycle, fuzzy decision trees are based on the algorithm of fuzzy ID3; in the feedback cycle, parameters of fuzzy decision trees are adapted based on stochastic gradient algorithm by traverse to the root nodes back from the leaves. Using this strategy, the hierarchical structure of the fuzzy decision trees remains fixed.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.