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Cluster Based Segmentation using K-Means Algorithm

  • International Journal of Data Mining Techniques and Applications
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Abstract

In this paper we present about Data Mining and brief detail about the clustering algorithm which is used to cluster categorical data. The algorithm called K means. The K means algorithm is capable of clustering large data sets. Clustering is used to measure the difference between objects by identifying the distance between the pair of objects. These measures include the Euclidean, Minkowski and Manhattan distance. In this paper we used Euclidean distance to measure the distance between objects. Segmentation is within our overall customer database, which ones have something in common. We need to find the groups of people, understand them and make some commercial value from the different groups

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DOI
10.20894/ijdmta.102.008.002.003
OpenAlex
W4376487386
Document type
article
Language
EN
Source
International Journal of Data Mining Techniques and Applications
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