Abstract—Data classification is the basic approach of data mining and Knowledge discovery in databases (KDD). In recent years, cloud classifier based on the cloud theory has been proposed. The most difference between cloud classifier and the traditional classifiers was that classified boundary of cloud classifier is fuzzy. Since current research only focus on the one-dimensional cloud generator algorithm, so this paper presents the classification algorithms based on the multi-dimensional cloud generator. Moreover, to resolve the complexity of classification which was brought by multi-dimension independent samples, the author proposes a method to so1ve the dimensionality reduction problem of multi-dimensional samples by one-dimensional cloud charts. Finally, the accuracy of cloud classifier is verified by a classification experiment on a texture database.

Index Terms—Cloud model, classification algorithm, dimensionality reduction

L. Qin and B. Li is with State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China.
L. Qin is with School of Science, Huazhong Agricultural University, Wuhan 430070, China (e-mail: qinli0606@126.com).
B. Li is with School of Computer, Wuhan University, Wuhan 430072,China.

Cite: Li Qin and Bing Li, "Research of the Multi-Dimensional Cloud Classification Algorithm," International Journal of Computer and Communication Engineering vol. 1, no. 1, pp. 59-61 , 2012.