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Customer Data Clustering using M.F.P to Improve the Performance of Sales and Marketing

Author(s):

C Lakshmi Devi , KMM Institute of PG Studies, Tirupati, India; Dr. K. Venkataramana, KMM Institute of PG Studies, Tirupati, India

Keywords:

Clustering, Hierarchical Clustering, Make Density based Clustering, Farthest First

Abstract

Bunching is the assignment of collection a lot of articles in a similar gathering that are more like each other than to those in different gatherings. The information mining in deals and showcasing encourages organizations to advance their most beneficial items and boost the benefit. This paper displays the examination and investigation of four bunching calculations that is Density Based grouping, Canopy, Farthest First and Hierarchical Clustering by utilizing Wholesale Customer dataset. The exhibitions of these calculations are looked at utilizing the execution assessment measurements, for example, Time taken to assemble, Number ofbunch, and Number of group occurrences. The exploratory outcomes demonstrate that Hierarchical Clustering and Farthest First produce preferable outcome over Make Density based and Canopy.

Other Details

Paper ID: IJSRDV7I10591
Published in: Volume : 7, Issue : 1
Publication Date: 01/04/2019
Page(s): 746-748

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