2022
DOI: 10.54379/jiasf-2022-1-1
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Abstract: In machine learning, distance measure plays an important role in defining the similarity between two data-items. In the paper, we discuss some of the drawbacks of distance measures (metrics) with their possibly induced clustering algorithms. Further, to overcome the drawbacks, we propose a novel intuitionistic fuzzy distance measure associated with generalized cesa´ro paranormed sequence space Cesq p(F). We also discuss some geometric properties of Cesq p(F). Moreover, the proposed distance measure is utilized… Show more

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