Computer Science ›› 2015, Vol. 42 ›› Issue (3): 261-265.doi: 10.11896/j.issn.1002-137X.2015.03.054

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Clustering with Mixed Condition Attributes Based on Average Mutual Information

LIU Jin-sheng   

  • Online:2018-11-14 Published:2018-11-14

Abstract: There is a great difference between the distances of mixed condition attributes parameter.The numeric condition attributes object with larger and law magnitude tends to be clustered only.With small and chaos magnitude,the cate-gorical condition attributes object which has obvious category characteristics will be ignored.A clustering algorithm based on average mutual information was proposed.First,the size of parameter category characteristics is quantified through entropy.Then,the similarity and the difference between category characteristics are measured according ave-rage mutual information of entropy.The magnitude between distances of numeric and categorical condition attributes parameter is unified.At last,the final clustering result is got by optimizing iterative adaptive process.The experimental results show that the proposed algorithm was high clustering quality and good adaptability.

Key words: Mixed condition attributes,Average mutual information,Clustering

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