Analysis of Clustering Algorithms in E-Commerce using WEKA

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Provided by: International Journal of Computer Science and Management Studies (IJCSMS)
Topic: Data Management
Format: PDF
Data clustering is a process of putting similar data into groups. A clustering algorithm partitions a data set into several groups such that the similarity within a group is larger than among groups. Moreover, most of the data collected in many problems seem to have some inherent properties that lend themselves to natural groupings. Clustering algorithms are used extensively not only to organize and categorize data, but are also useful for data compression and model construction. This paper reviews on types of clustering techniques K-means clustering, hierarchical clustering, DBScan clustering, optics and EM algorithm.
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