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Economic Performance Classification Using Neural Networks

Adrian Costea, Economic Performance Classification Using Neural Networks. In: Ion Ivan, Ion-Gheorghe Rosca (Eds.), Proceedings of the Sixth International Symposium on Economic Informatics, Bucharest, Romania, May 8-1, Academy of Economic Studies, 2003.

Abstract:

In this paper we propose a new approach for assessing countries economic performance. In our two-level methodology we combine an unsupervised learning technique (SOM) with a supervised classical neural network algorithm in order to assess central-eastern European countries economic performance. The sub-goal of the paper is to find the best supervised training algorithm for the second phase of our methodology and, at the same time, the best topology of the supervised neural network. We also compare the performance of supervised neural network used as classifier with the performance of other classifiers applied on the same data in our previous work.

BibTeX entry:

@INPROCEEDINGS{inpCostea03a,
  title = {Economic Performance Classification Using Neural Networks},
  booktitle = {Proceedings of the Sixth International Symposium on Economic Informatics, Bucharest, Romania, May 8-1},
  author = {Costea, Adrian},
  editor = {Ivan, Ion and Rosca, Ion-Gheorghe},
  publisher = {Academy of Economic Studies},
  year = {2003},
}

Belongs to TUCS Research Unit(s): Data Mining and Knowledge Management Laboratory

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