Linear Combination of Neural Networks Using Particle Swarm Optimization
Publish place: 11th Annual Conference of Computer Society of Iran
Publish Year: 1384
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ACCSI11_229
تاریخ نمایه سازی: 5 آذر 1390
Abstract:
This paper presents a new way of computing the weights for combining multiple neural network classifiers based on particle swarm optimization (PSO). The weights are obtained so that they minimize the total classification error rate of an ensemble system. In order to evaluate the effectiveness of the proposed method, we have carried out some experiments on two benchmark data sets: Satimage and Phoneme. Experimental results show that PSO-based weighting method outperforms the MSE and simple averaging methods
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Authors
S.H. Nabavi-Kerizi
Dept. of Electrical Eng. Tarbiat Modares University
M. Abadi
Dept. of Computer Eng. Tarbiat Modares University
E. Kabir
Dept. of Electrical Eng. Tarbiat Modares University