The cluster validity is an important topic of cluster analysis, which is often converted into the determination of the optimal cluster number. Most of the available cluster validity functions are limited for the analysis of numeric data set and ineffective for the categorical data set. For this purpose, a new cluster validity function is presented in this paper, namely the modified partition fuzzy degree. By combining the partition entropy and the partition fuzzy degree, the new cluster validity can be applied to any data set with numeric attributes or categorical attributes. The experimental results illustrate the effectiveness of the proposed cluster validity function.
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