HIMIC : A Hierarchical Mixed Type Data Clustering Algorithm
نویسندگان
چکیده
Clustering is an important data mining technique. There are many algorithms that cluster either numeric or categorical data. However few algorithms cluster mixed type datasets with both numerical and categorical attributes. In this paper, we propose a similarity measure between two clusters that enables hierarchical clustering of data with numerical and categorical attributes. This similarity measure is derived from a frequency vector of attribute values in a cluster. Experimental results establish that our algorithm produces good quality clusters.
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