Abstract
In this paper, a liver disease diagnosis is carried out using quantum-based binary neural network learning algorithm (QBNN-L). The proposed method constructively form the neural network architecture, and weights are decided by quantum computing concept. The use of quantum computing improves performance in terms of number of neurons at hidden layer and classification accuracy and precision. Same is compared with various classification algorithms such as logistic, linear logistic regression, multilayer perceptron, support vector machine (SVM). Results are showing improvement in terms of generalization accuracy and precision.
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Patel, O.P., Tiwari, A. (2015). Liver Disease Diagnosis Using Quantum-based Binary Neural Network Learning Algorithm. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 336. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2220-0_34
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DOI: https://doi.org/10.1007/978-81-322-2220-0_34
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