DATE: Mon, June 8, 2015
TIME: 11:00 pm
PLACE: SITE 5084
TITLE: Neutrosophic Classifier: An extension of Fuzzy Classifier
PRESENTER: Swati Aggarwal
University of Delhi
ABSTRACT:

Fuzzy classification has become of great interest because of its ability to utilize simple linguistically interpretable rules and has overcome the limitations of symbolic or crisp rule based classifiers. A Neutrosophic classifier is an extension to fuzzy classifier; which utilizes Neutrosophic logic for its working. Neutrosophic logic is a generalized logic that is capable of effectively handling indeterminacy, stochasticity acquisition errors that fuzzy logic cannot handle. Neutrosophic classifier has been tested on the Iris dataset and results generated are compared with the commonly used fuzzy classifiers on the following parameters: nature of membership functions, number of rules and indeterminacy in the results generated. Though Neutrosophic logic is in its nascent stage still it holds the potential to be experimented for further exploration in different domains.

Bio: Swati Aggarwal did her Ph.D from at the Central University Jamia Millia Islamia, New Delhi. She has done B.Tech (Computer Science) and M.Tech (Information Technology). Currently she is working as an Assistant Professor in Computer Engineering Department of NSIT, An Autonomous Institution under Govt. of NCT of Delhi and affiliated to University of Delhi, India. Her interests include Neutrosophic Logic, Fuzzy sets, Artificial intelligence, Neural network, Machine learning and other Soft computing based techniques.