Classification using Neutrosophic Logic - Bhutani, Kanika
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Fuzzy classification is very necessary because it has the ability to use interpretable rules. It has got control over the limitations of crisp rule based classification. This book mainly deals with classification using fuzzy probability and Neutrosophic probability. Classification based on Neutrosophic probability employs Neutrosophic logic and Neutrosophic probability for its working and is compared with classification based on fuzzy probability on the basis of parameters such as probability and ambiguity in the results. Classification based on fuzzy and Neutrosophic probability are…mehr

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Produktbeschreibung
Fuzzy classification is very necessary because it has the ability to use interpretable rules. It has got control over the limitations of crisp rule based classification. This book mainly deals with classification using fuzzy probability and Neutrosophic probability. Classification based on Neutrosophic probability employs Neutrosophic logic and Neutrosophic probability for its working and is compared with classification based on fuzzy probability on the basis of parameters such as probability and ambiguity in the results. Classification based on fuzzy and Neutrosophic probability are implemented on appendicitis dataset from Knowledge extraction based on evolutionary learning.
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Autorenporträt
Kanika Bhutani is a dedicated professional. She is working as an Assistant Professor at NIT Kurukshetra. She has done B.Tech from Maharshi Dayanand University, Rohtak and completed her M.Tech (Silver Medalist) from The ITM University, Gurgaon. She has guided many B.Tech projects. Her interests are fuzzy logic, neutrosophic logic, CI etc.