Dynamic classifier combination using neural network

1995 ◽  
Author(s):  
Dar-Shyang Lee ◽  
Sargur N. Srihari
Keyword(s):  
Neural Network ◽  
Classifier Combination

Classifier Combination and Selection Methods at the Corporate Bankruptcy Prediction

2017 ◽  
Vol 64 (2) ◽  
pp. 177-192
Author(s):  
Bartłomiej Lach
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Logistic Regression ◽  
Discriminant Analysis ◽  
Bankruptcy Prediction ◽  
Classifier Combination ◽  
Correct Classification ◽  
Selection Methods ◽  
Corporate Bankruptcy ◽  
Linear Discriminant

The author of this article decided to investigate the efficiency of using classifier combination and selection methods at the prediction of corporate bankruptcy in Poland. The study allowed us to compare the predictions from 4 individual classifiers: linear discriminant analysis, logistic regression, artificial neural network and random forest with the predictions from 9 classifier combination and selection methods. Moreover, the author analyzed the influence of the number of variables in models on performances of the correct classification for all considered methods.

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Analysis ◽  
Renal Stones ◽  
Neural Network Analysis ◽  
Artificial Neural Network Analysis ◽  
Artificial Neural
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