K-Means Clustering In R

Raghavan Madabusi provides an example of how k-means clustering can help segment data points in an understandable manner:

Call Detail Record (CDR) is the information captured by the telecom companies during Call, SMS, and Internet activity of a customer. This information provides greater insights about the customer’s needs when used with customer demographics. Most of the telecom companies use CDR information for fraud detection by clustering the user profiles, reducing customer churn by usage activity, and targeting the profitable customers by using RFM analysis.

In this blog, we will discuss about clustering of the customer activities for 24 hours by using unsupervised K-means clustering algorithm. It is used to understand segment of customers with respect to their usage by hours.

For example, customer segment with high activity may generate more revenue. Customer segment with high activity in the night hours might be fraud ones.

This article won’t really explain k-means clustering in any detail, but it does give you an example to apply the technique using R.

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