Optimum complexity neural networks for anomaly detection task
Abstract
In this paper we study the performance of compressed data for classification and anomaly detection. We use networks of various complexities for our purpose, guided by the data itself rather than one uniform-complexity network for the entire data set.
Publication Title
Proceedings of the International Joint Conference on Neural Networks
Recommended Citation
Kozma, R., Majumdar, N., & Dasgupta, D. (2002). Optimum complexity neural networks for anomaly detection task. Proceedings of the International Joint Conference on Neural Networks, 2, 1138-1142. Retrieved from https://digitalcommons.memphis.edu/facpubs/3055
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