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.
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