Adjust and Explain the Clustering Results of Categorical Data
Baojia Li, Yongqian Liu · 2010
With the improvement of the information enriching and sharing, it is possible and valuable to increase the information content of the clustering results referencing external information. A method to adjust clustering results categorical data referencing an external set is put forward. From the applied point of view, it is very important to explain correctly the meaning of clustering results. The approach explain the meaning of clustering results with the help calculating the ratio of frequency is given. The effectiveness the method is illustrated by the numeric experiments. Lastly, some problems that will be studied further are pointed out.