An Intuitionistic Fuzzy C-Means Clustering Algorithm with Point Symmetry Distance Measure

Provided by: International forum of researchers Students and Academician
Topic: Data Management
Format: PDF
Clustering is a fundamental problem in data mining with innumerable applications spanning many fields. In organize to scientifically recognize clusters in a data set, it is typically essential to initial describe a measure of resemblance or nearness which will set up a rule for transmission patterns to the area of an exacting cluster centroid. One of the essential features of shapes and objects is evenness. The planned algorithm accepts a research non-metric distance measure founded on the idea of "Point symmetry".

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