Abstract

With a focus on classification problem, in this paper, we present an integrated approach to improve the performance of classification using adaptive resonance theory (ART) neural network and logistic regression classifiers. In our approach, the neural network classifier is trained first and then regression analysis is applied to each individual class. In testing phase, the data is applied to the regression classifier and, if any deviation exists, the neural network classifier is retrained. The study reveals that effective data mining can be achieved by combining the power of neural networks with the rigor of more traditional statistical tools.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.