8.txt

来自「This complete matlab for neural network」· 文本 代码 · 共 31 行

发信人: helloboy (hello), 信区: DataMining
标  题: Decision Tree&Neural Network
发信站: 南京大学小百合站 (Thu Aug 22 09:53:41 2002), 站内信件

C-Net: A Method for Generating Non-deterministic and Dynamic Multivariate De
cision Trees

Abstract:
Abstract. Despite the fact that artificial neural networks (ANNs) are univer
sal function approximators, their black box nature (that is, their lack of d
irect interpretability or expressive power) limits their utility. In contras
t, univariate decision trees (UDTs) have expressive power, although usually 
they are not as accurate as ANNs. We propose an improvement, C-Net, for both
 the expressiveness of ANNs and the accuracy of UDTs by consolidating both t
echnologies for generating multivariate decision trees (MDTs). In addition, 
we introduce a new concept, recurrent decision trees, where C-Net uses recur
rent neural networks to generate an MDT with a recurrent feature. That is, a
 memory is associated with each node in the tree with a recursive condition 
which replaces the conventional linear one. Furthermore, we show empirically
 that, in our test cases, our proposed method achieves a balance of comprehe
nsibility and accuracy intermediate between ANNs and UDTs. MDTs are found to
 be intermediate since they are more expressive than ANNs and more accurate 
than UDTs. Moreover, in all cases MDTs are more compact (i.e., smaller tree 
size) than UDTs.

http://springer.lib.tsinghua.edu.cn/app/home/contribution.asp?wasp=e05d217q
mq2t1dkt9t0m&referrer=parent&backto=issue,4,7;journal,6,11;subject,23,40;

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