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K-Means for Categorical Data Clustering by Kiran Keeru is a document available to read on EtoBox.

What is K-Means for Categorical Data Clustering about?

This document discusses clustering categorical data using the k-means algorithm. Specifically, it proposes transforming categorical values into numeric ones using the relative frequency of each category in the attributes. This approach is compared to transforming categorical data into binary values. The paper aims to experiment the scalability and accuracy of the two methods for clustering categorical data, with the goal of outperforming the binary transformation approach. It provides background on clusteri

Author

Kiran Keeru

Language

EN