Paper Abstract and Keywords |
Presentation |
2004-11-19 14:15
An new method for efficient design of neural network trees Qiangfu Zhao (U-Aizu) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Neural network tree (NNTree) is a hybrid learning model with the
overall structure being a decision tree (DT), and each non-terminal
node containing an expert neural network (ENN). Generally speaking,
NNTrees outperform conventional DTs because more complex and
possibly better features can be extracted by the ENNs. So far we
have studied several genetic algorithms (GAs) for designing the
NNTrees. These algorithms, however, are computationally expensive,
and cannot be used easily. In this paper, we propose a new approach
based on the R4-rule, which is a non-genetic evolutionary
algorithm proposed by the author several years ago. The key point
is to propose a heuristic method for defining the teacher signals
for the examples assigned to a non-terminal node. Once the teacher
signals are defined, the ENNs can be trained quickly using the
R4-rule. Experiments with several public databases show that the
new approach can produce NNTrees quickly and effectively. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Neural network / decision tree / neural network tree / nearest neighbor classifier / the R4-rule / / / |
Reference Info. |
IEICE Tech. Rep., vol. 104, no. 448, PRMU2004-115, pp. 59-64, Nov. 2004. |
Paper # |
PRMU2004-115 |
Date of Issue |
2004-11-12 (PRMU) |
ISSN |
Print edition: ISSN 0913-5685 |
Download PDF |
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Conference Information |
Committee |
PRMU |
Conference Date |
2004-11-18 - 2004-11-19 |
Place (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
PRMU |
Conference Code |
2004-11-PRMU |
Language |
English (Japanese title is available) |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
An new method for efficient design of neural network trees |
Sub Title (in English) |
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Keyword(1) |
Neural network |
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decision tree |
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neural network tree |
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nearest neighbor classifier |
Keyword(5) |
the R4-rule |
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1st Author's Name |
Qiangfu Zhao |
1st Author's Affiliation |
The University of Aizu (U-Aizu) |
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Speaker |
Author-1 |
Date Time |
2004-11-19 14:15:00 |
Presentation Time |
30 minutes |
Registration for |
PRMU |
Paper # |
PRMU2004-115 |
Volume (vol) |
vol.104 |
Number (no) |
no.448 |
Page |
pp.59-64 |
#Pages |
6 |
Date of Issue |
2004-11-12 (PRMU) |
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