DocumentCode :
569385
Title :
The Research on Discretization Algorithm Based on Dynamic Hierarchical Clustering
Author :
Li, Xiao Fei
Author_Institution :
Dept. Math. & Comput., Wu Yi Univ., Wuyi, China
fYear :
2012
fDate :
17-19 Aug. 2012
Firstpage :
349
Lastpage :
352
Abstract :
The discretization problem of continuous attribute is an important topic of machine learning, and data preprocessing. The discretization algorithm based on dynamic hierarchical clustering proposed in the paper is an improvement of hierarchical clustering algorithm. First, the qualitative analysis of the algorithm is made. Second, clustering analysis of the random collection data according to the similarity degree is described and a kind of division on the domain is received. Indicated by the experiment, the discretization algorithm based on dynamic hierarchical clustering could be more reasonable and efficient to the division of continuous attribute.
Keywords :
data analysis; learning (artificial intelligence); pattern clustering; continuous attribute; data preprocessing; discretization algorithm; dynamic hierarchical clustering; machine learning; qualitative analysis; random collection data; similarity degree; Algorithm design and analysis; Clustering algorithms; Decision making; Educational institutions; Heuristic algorithms; Machine learning algorithms; Rough sets; continuous attribute discretization dynamic hierarchical clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
Type :
conf
DOI :
10.1109/ICCIS.2012.347
Filename :
6300508
Link To Document :
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