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Additional info for Artificial Intelligence and Innovations 2007: from Theory to Applications: Proceedings of the 4th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2007)
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The problem been analyzed using many algorithms like branch-and-bound, greedy searching algorithms etc. In recent years, the genetic algorithms been used for analyzing this problem widely [1]. We can assume this problem as an undirected graph problem. In this problem, we are searching for minimum path where visits all the nodes exactly once and finishes at the node start from that. Figl indicates an example with its optimal solution. A, B, C... are the cities and the numbers on the edges are the cost of links [1].
ACM Press. 7. , Zhang, J. K. (1999). AdaCost: Misclassification costsensitive boosting. Proceedings of the Sixteenth International Conference on Machine Learning, 97-105. San Francisco: Morgan Kaufinann. 8. Japkowicz N. (2000), The class imbalance problem: Significance and strategies. In Proceedings of the International Conference on Artificial Intelligence, Las Vegas. 9. Japkowicz N. and Stephen, S. (2002), The Class Imbalance Problem: A Systematic Study Intelligent Data Analysis, Volume 6, Number 5.
And Provost F. (1997), Adaptive Fraud Detection. Data Mining and Knowledge Discovery, 1(3):291-316. Friedman J. H. (1997), On bias, variance, 0/1-loss and curse-of-dimensionality. Data Mining and Knowledge Discovery, 1: 55-77. , Lavrac, N. & Dzeroski, S. (2000). Noise Detection and Elimination in Data Preprocessing: experiments in medical domains. Applied Artificial Intelligence 14, 205-223. Japkowicz N. (2000), The class imbalance problem: Significance and strategies. In Proceedings of the International Conference on Artificial Intelligence, Las Vegas.
