Analysis of Neural Networks Illogical Behavior in Classification Problems at the Environmental Monitoring of Water Bodies
| Autor: | T. R. Zhangirov, A. A. Liss, S. A. Ivanova, A. S. Perkov, A. V. Ekalo, N. Y. Grigoryeva |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Artificial neural network Generalization business.industry Process (engineering) Computer science 02 engineering and technology Linear discriminant analysis Machine learning computer.software_genre ComputingMethodologies_PATTERNRECOGNITION 020901 industrial engineering & automation Environmental monitoring 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | 2019 XXII International Conference on Soft Computing and Measurements (SCM)). |
| DOI: | 10.1109/scm.2019.8903807 |
| Popis: | The problem of illogical behavior of classifying neural networks, arising in the tasks of environmental monitoring of reservoirs, is considered. The paper presents the original method of analyzing neural networks, which allows to identify illogical behavior, i.e., false-positive results of classification and generalization. The problem of generalization of observations, belonging to classes not involved in training process, the so-called problem of external generalization problem, is analyzed. In the framework of the proposed technique methodology, a method for verification of training quality for a classifying neural network is considered, based on a comparison of the results of classification with the results of linear discriminant analysis. Implementation of the developed technique was performed for current ecological problem - classification of blue-green algae according to the self-fluorescence spectra during toxical “bloom” of water bodies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|