Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4712
Title: Liver disease diagnosis using quantum-based binary neural network learning algorithm
Authors: Tiwari, Aruna
Keywords: Algorithms;Diagnosis;Network architecture;Problem solving;Quantum computers;Soft computing;Support vector machines;Binary neural networks;Classification accuracy;Classification algorithm;Generalization accuracy;Hidden layers;Logistic regressions;Multi layer perceptron;Quantum Computing;Learning algorithms
Issue Date: 2015
Publisher: Springer Verlag
Citation: Patel, O. P., & Tiwari, A. (2015). Liver disease diagnosis using quantum-based binary neural network learning algorithm doi:10.1007/978-81-322-2220-0_34
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. © Springer India 2015.
URI: https://doi.org/10.1007/978-81-322-2220-0_34
https://dspace.iiti.ac.in/handle/123456789/4712
ISBN: 9788132222194
ISSN: 2194-5357
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: