Divide and ConquerMethod for Clustering Mixed Numerical and Categorical Data

Provided by: International Journal of Computer Science and Information Technologies
Topic: Data Management
Format: PDF
Clustering is a challenging task in data mining technique. The aim of clustering is to group the similar data into number of clusters. Various clustering algorithms have been developed to group data into clusters. The main aim of cluster analysis is to assign objects into groups (clusters) in such a way that two objects from the same cluster are more similar than two objects from different clusters. Various clustering algorithms have been developed to group data into clusters in diverse domains. However, these clustering algorithms work effectively either on pure numeric data or on pure categorical data, most of them perform poorly on mixed categorical and numeric data types.

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