Neutrosophic classifier: An extension of fuzzy classifer

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. This paper introduces an extension to fuzzy classifier: a neutrosophic classifier, which would utilize 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. The proposed neutrosophic classifier employs neutrosophic logic for its working and is an extension of commonly used fuzzy classifier. It is compared with the commonly used fuzzy classifiers on the following parameters: nature of membership functions, number of rules and indeterminacy in the results generated. It is proved in the paper that extended fuzzy classifier: neutrosophic classifier; optimizes the said parameters in comparison to the fuzzy counterpart. Finally the paper is concluded with justifying that neutrosophic logic though in its nascent stage still holds the potential to be experimented for further exploration in different domains.

Synergy of linguistic summaries and fuzzy functional dependencies for mining knowledge in the data

“…In such case, a class with clear boundaries represents only an oversimplification of reality, which the fuzzy logic approach seems to handle easily [2]. Furthermore, according to [11] "data summarization is one of basic capabilities needed by any 'intelligent' system.…”

Generalization of Fuzzy C-Means based on Neutrosophic Logic

“…That is the knowledge that comes from human observation is mostly characterized by imprecise data, as a result of the imprecision of humans [4]. Therefore, NL is perfect in treating problems that have imprecision, uncertainty, partial truth, incompleteness, or inconsistency in data.…”

“…However, in real-world applications, it is difficult to use this non-standard unit interval. Therefore in applications, the non-standard unit interval is replaced by the standard real interval [0,1] [4].…”

Neutrosophic Concept Lattice based Approach for Computing Human Activities from Contexts

“…As with fuzzy logic, falsity dominates in conjunction and truthness in disjunction. Neutrosophic logic has been used to extend fuzzy classification in [20]. In this work, we make use of neutrosophic logic to extend our FCA based activity model.…”

“…One significant work towards use of neutrosophic logic has been presented in [20], where neutrosophic logic based extension of fuzzy classifier has been designed. Although, fuzzy concept lattices have been worked upon by many researchers, this is the first attempt to further generalize concept lattices with neutrosophic logic.…”