Dependence of Two Different Fuzzy Clustering Techniques on Random Initialization and a Comparison

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Provided by: Creative Commons
Topic: Big Data
Format: PDF
Clustering is a technique by means of which a large dataset is partitioned into some smaller groups, called clusters, using some similarity measures, such that the similarity between any two objects in the same group is more than that between two objects in two different groups. In conventional hard clustering an object either fully belongs to a particular cluster or does not belong to it at all. In the recent past Kernelized Fuzzy C-Means clustering technique has earned popularity especially in the machine learning community.
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