Quantum-Behaved Particle Swarm Optimization Based Radial Basis Function Network for Classification of Clinical Datasets
| Autor: | N. Leema, Arputharaj Kannan, H. Khanna Nehemiah |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Information Systems and Management
Radial basis function network Mean squared error Artificial neural network Computer Networks and Communications business.industry Computer science Particle swarm optimization 020206 networking & telecommunications Pattern recognition 02 engineering and technology Computer Science Applications Management Information Systems Computational Theory and Mathematics Approximation error 0202 electrical engineering electronic engineering information engineering Cluster (physics) 020201 artificial intelligence & image processing Artificial intelligence business Cluster analysis Classifier (UML) Information Systems |
| Zdroj: | International Journal of Operations Research and Information Systems. 9:32-52 |
| ISSN: | 1947-9336 1947-9328 |
| DOI: | 10.4018/ijoris.2018040102 |
| Popis: | In this article, a classification framework that uses quantum-behaved particle swarm optimization neural network (QPSONN) classifiers for diagnosing a disease is discussed. The neural network used for classification is radial basis function neural network (RBFNN). For training the RBFNN K-means clustering algorithm and quantum-behaved particle swarm optimization (QPSO) algorithm has been used. The K-means clustering algorithm is used to find the optimal number of clusters which determines the number of neurons in the hidden layer. The cluster approximation error is used to find the optimal clusters. The weights between the hidden and the output layer is determined using QPSO algorithm based on the mean squared error (MSE). The performance of the developed classifier model has been tested with five clinical datasets, namely Pima Indian Diabetes, Hepatitis, Bupa Liver Disease, Wisconsin Breast Cancer and Cleveland Heart Disease were obtained from the University of California, Irvine (UCI) machine learning repository. |
| Databáze: | OpenAIRE |
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