Sharkey, A.J.C.: Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems. London: Springer. (1999) Home/Search Document Not in Database Summary Related Articles Check |
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A New Learning Scheme for Neural Network Ensembles - Haraldsson, Ohlsson (2002) (Correct)
....found in the work of Liu [8] Another approach was taken by Rosen [9] where an error correlation penalty term was added to the network error function to reduce the correlations of individual network errors. More developments and good selections of important ensemble research can be found in [4] [10] and [11] Since neural network ensembles are easy to use and give better performance than single neural networks models, they are also used in real world applications. From the medical domain one can find lung cancer cell identification [12] diagnosis of breast cancer [13] diagnosis of small ....
A. Sharkey, Ed., Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems. London: Springer-Verlag, 1999.
Co-Operative Neural Networks and `integrated' Classification - Ahmad, Vrusias, Tariq (2002) (Correct)
.... was used in the simulation of language disorders using cooperative modular connectionist networks, in which semantic lexical and phonological knowledge are instantiated using self organising Kohonen maps, while connections between them are implemented using Hebbian networks [5] Sharkey [11] has categorised multi nets as systems that either comprise ensembles or modular combinations of neural networks: In an ensemble combination, the component nets are redundant in that they each provide a solution to the same task, or task component, even though this solution might be obtained by ....
Sharkey, A.J.C (Ed.) "Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, Springer-Verlag London Limited", 1999.
Medical Diagnosis with C4.5 Rule Preceded by Artificial Neural.. - Zhou, Jiang (2003) (Correct)
....multiple artificial neural networks are trained to solve the same problem. Since the generalization ability of learning systems based on artificial neural networks can be significantly improved with this technique, it has become a hot topic in both machine learning and neural computing communities [27] and has already been tried in several medical tasks [6] 28] 31] However, since an ensemble is composed of multiple artificial neural networks, its comprehensibility is even worse than that of a single artificial neural network, which may hinder the wide acceptance of this technique in ....
....systems based on artificial neural networks can be significantly improved through ensembling artificial neural networks, i.e. training multiple artificial neural networks and combining their predictions. Subsequently there appears a hot wave in investigating artificial neural network ensembles [27], and this technique has already been successfully applied to diverse domains such as optical character recognition [7] 11 ] 17] face recognition [10] 14] scientific image analysis [4] seismic signals classification [29] etc. In general, an artificial neural network ensemble is built ....
D. Sharkey, Ed. Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems. London: Springer-Verlag, 1999.
Ensembles of Learning Machines - Valentini, Masulli (2002) (2 citations) (Correct)
....meaning, in order to include the whole range of combining methods. This variety of terms and specifications reflects the absence of an unified theory on ensemble methods and the youngness of this research area. However, the great e#ort of the researchers, reflected by the amount of the literature [118, 70, 71] dedicated to this emerging discipline, achieved meaningful and encouraging results. Empirical studies showed that both classification and regression problem ensembles are often much more accurate than the individual base learner that make them up [8, 29, 40] and recently di#erent theoretical ....
A. Sharkey (editor). Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems. Springer-Verlag, London, 1999.
Genetic Algorithm based Selective Neural Network Ensemble - Zhou, Wu, Jiang, Chen (2001) (2 citations) (Correct)
....should be further explored. 5 Related Works Neural network ensemble has become a very active area and there are a large number of research groups working on it. Besides the achievements cited in the brief review presented in Section 1, some significant developments in this area can be found in [Sharkey, 1999]. Moreover, there are some works very related to this paper. Yao and Liu [1998] employed genetic algorithm to evolve a population of neural networks. Instead of choosing the best neural network in the last generalization as the final result, they regarded the entire population as a neural network ....
D. Sharkey, editor. Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, Springer-Verlag, London, 1999.
Lung Cancer Cell Identification Based on Artificial.. - Zhou, Jiang, Yang, Chen. (2002) (4 citations) (Correct)
....where all the individual networks were trained simultaneously through the correlation penalty terms in their error functions. Chan [3] presented weighted least square ensemble that did not require that the individual networks were independent. More developments in this area can be found in [24]. Since artificial neural network ensembles work remarkably well and are easy to be used, they are regarded as a promising methodology that can profit not only experts in artificial neural network research but also engineers in real world applications. Besides Hansen et al. s work in handwritten ....
Sharkey D editor. Combining artificial neural nets: Ensemble and modular multi-net systems. London: Springer-Verlag, 1999.
The "test and Select" Approach to Ensemble Combination - Amanda Sharkey Noel (2000) (7 citations) Self-citation (Sharkey) (Correct)
....a combination of several This essentially is the reasoning behind the idea of multiple classifier systems, and it is an idea that is relevant both to neural computing, and to the wider machine learning community. In this paper, we are primarily concerned with the development of multi net systems [1], i.e. combinations of Artificial Neural Nets (ANNs) We shall focus on ensemble combinations of neural nets; providing an overview of methods 0 G.O.Chandroth is now at Lloyds Register, but his contribution to this paper was made whilst he was at University of Sheffield 0 We would like to thank ....
Sharkey, A.J.C. (1999) Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems. London, Springer-Verlag.
Vibration Signatures, Wavelets and Principal Components.. - Chandroth Sharkey.. Self-citation (Sharkey) (Correct)
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Sharkey, A.J.C., (eds.), Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, Springer-Verlag, London, 1999.
Combining Multiple Classifiers to Improve Part of - Speech Tagging Case (2000) (Correct)
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Sharkey, A.J.C.: Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems. London: Springer. (1999)
An Ensemble Of Neural Networks For Weather Forecasting - Maqsood, Khan, Abraham (2004) (Correct)
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Sharkey AJC (1999) Combining artificial neural nets: ensemble and modular multi-net systems. Springer, Berlin Heidelberg New York
Switching Class Labels to Generate Classification Ensembles - Martínez-Muñoz, Suárez (2005) (Correct)
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A. J. C. Sharkey, Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, Springer-Verlag, London, 1999.
Aggregation Ordering in Bagging - Martínez-Muñoz, Suárez (2004) (Correct)
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A.J.C. Sharkey, Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, (London, Springer-Verlag, 1999 )
Automatic Multi-Module Neural Network Evolution in.. - Dinerstein.. (2002) (1 citation) (Correct)
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A. Sharkey. Combining Artificial Neural Nets: Ensemble and Modular Multi--Net Systems. Springer-Verlag, London, UK, 1999.
Analysis of the Correlation between Majority Voting Error and.. - Ruta, Gabrys (2001) (Correct)
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Sharkey AJC. Combining artificial neural nets: ensemble and modular multi-net systems. Springer-Vorlag, Berlin, 1999.
Prediction of the CATS benchmark exploiting - Time-Reversal Symmetry Verdes (Correct)
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A. J. C. Sharkey, editor, Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, Springer-Verlag, London, 1999.
A Theoretical Analysis of the Limits of Majority Voting Errors .. - Ruta, Gabrys (2000) (1 citation) (Correct)
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Sharkey AJC. Combining artificial neural nets: ensemble and modular multi-net systems. Springer-Vorlag, Berlin, 1999.
Physical Field Models for Pattern Classification - Ruta, Gabrys (Correct)
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Sharkey AJC (1999) Combining artificial neural nets: ensemble and modular multi-net systems. Springer-Verlag, Berlin Heidelberg New York.
New Measure of Classifier Dependency in Multiple Classifier.. - Ruta, Gabrys (2002) (Correct)
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Sharkey A.J.C.: Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems. Springer-Verlag, Berlin Heidelberg New York (1999).
Set Analysis of Coincident Errors and Its Applications for.. - Ruta, Gabrys (Correct)
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Sharkey A.J.C. Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems. Springer-Verlag, Berlin Heidelberg New York (1999).
Static Field Approach for Pattern Classification - Ruta, Gabrys (Correct)
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Sharkey A.J.C.: Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems. Springer-Verlag, Berlin Heidelberg New York (1999).
The Boundaries of Knowledge - Ruta, Gabrys (Correct)
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Sharkey A.J.C.: Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems. Springer-Verlag, Berlin Heidelberg New York (1999).
Application of the Evolutionary Algorithms for Classifier.. - Ruta, Gabrys (2001) (1 citation) (Correct)
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Sharkey A.J.C.: Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems. Springer-Verlag, Berlin Heidelberg New York (1999)
Diversity Creation Methods: A Survey And Categorisation - Brown, Wyatt, Harris, Yao (2004) (3 citations) (Correct)
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A. Sharkey, Multi-Net Systems, Springer-Verlag, 1999, Ch. Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, pp. 1--30.
Feature Selection and Classifier Ensembles: A Study on.. - Yu (2003) (Correct)
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Amanda J. C. Sharkey, editor. Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems (Perspectives in Neural Computing). Springer Verlag, Apr. 1999. 23
Studies of Model Selection and Regularization for Generalization in .. - Guo (Correct)
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Amanda J.C. Sharkey, Ed., Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems , Springer, London; New York, 1999.
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