Implementation of Clustering Algorithms in RapidMiner

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Provided by: International forum of researchers Students and Academician
Topic: Big Data
Format: PDF
Clustering can be used for data mining, information retrieval, text mining, web analysis and marketing etc. There are various Clustering algorithms but the authors have implemented three algorithms (K-means, DBScan and K-medoids) in RapidMiner. In data mining, Clustering can be considered as the most unsupervised learning techniques. Clustering is a process of grouping a set of physical (or abstract) objects into class whose members are similar in some way. A cluster is therefore a collection of objects which are similar between them and are dissimilar to the object belonging to other cluster. In this paper, the implementation of clustering algorithms in RapidMiner is discussed.
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