Role Of Neutrosophic Logic In Data Mining


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Role of Neutrosophic Logic in Data Mining


Role of Neutrosophic Logic in Data Mining

Author: KALYAN MONDAL

language: en

Publisher: Infinite Study

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This paper presents a data mining process of single valued neutrosophic information. This approach gives a presentation of data analysis common to all applications. Data mining depends on two main elements, namely the concept of similarity and the machine learning framework. It describes a lot of real world applications for the domains namely mathematical, medical, educational, chemical, multimedia etc.

Machine learning in Neutrosophic Environment: A Survey


Machine learning in Neutrosophic Environment: A Survey

Author: Azeddine Elhassouny

language: en

Publisher: Infinite Study

Release Date:


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Veracity in big data analytics is recognized as a complex issue in data preparation process, involving imperfection, imprecision and inconsistency. Single-valued Neutrosophic numbers (SVNs), have prodded a strong capacity to model such complex information. Many Data mining and big data techniques have been proposed to deal with these kind of dirty data in preprocessing stage. However, only few studies treat the imprecise and inconsistent information inherent in the modeling stage. However, this paper summarizes all works done about mapping machine learning algorithms from crisp number space to Neutrosophic environment. We discuss also contributions and hybridization of machine learning algorithms with Single-valued Neutrosophic numbers (SVNs) in modeling imperfect information, and then their impacts on resolving reel world problems. In addition, we identify new trends for future research, then we introduce, for the first time, a taxonomy of Neutrosophic learning algorithms, clarifying what algorithms are already processed or not, which makes it easier for domain researchers.