Posted On: Feb 25, 2020
Clustering in Bigdata is a well-established unsupervised data mining approach that groups data points based on similarities. Clustering entities will give insights into the characteristics of different groups and results in the minimization of the dimensionality of data set when you are dealing with a myriad number of data. The higher the homogeneity within the cluster and the higher the differences between the clusters, the finer the cluster will be. Clusters are mainly of two types; soft clustering, based on the probability that a data point will belong to a specific cluster and, hard clustering, data points are separated into independent clusters. Among hundreds of clustering algorithms, they can be labeled into one of the following models such as connectivity, density, distribution, and centroid model.
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Big Data is a term related to large and complex data sets. Big Data is required in order to manage and perform different operation on a wide set of data...