A New Tool to Solve Machine Learning Problems under Intuitionistic Fuzzy Sets

Abstract

The focus of this manuscript is to develop fuzzy new information measure for IFSs, and we proved the reliability and validity of the introduced measure. There are many applications of divergence measures in machine learning are discussed by various well-known authors and researchers in the literature of Information Theory, Mathematics, Computer Science other branches of engineering. Here, proposed a new information and fuzzy divergence measure along AIFSs. Properties and their validity, we proved of the established fuzzy information and divergence measure in terms of fuzzy. Using similarity information measure under AIFSs, we shown the applications to deal the machine learning cases for real life problems or case study and justify by numerical illustrations and we also shown the comparisons along with other measures.

Two Trigonometric Intuitionistic Fuzzy Similarity Measures

“…Recently in 2021, Harish Garg and Dimple Rani (Garg & Rani, 2021) presented a novel similarity measure which is formed from the concept of transformation of Right-angled techniques and its characteristics. To tackle with the machine learning problems, Saraswat and Gahlot (Saraswat & Gahlot, 2021) invented a new similarity measure and applied the results to pattern recognition.…”