Title :
A brief study on clustering methods: Based on the k-means algorithm
Author :
Master, Chen Peng ; Professor, Xu Guiqiong
Author_Institution :
School of Management Shanghai University, SHU Shanghai, China
Abstract :
Clustering is the process of grouping a set of objects into classes. The clustering problem has been addressed by researchers in many contexts and disciplines. First, a process model for data mining and the typical requirements of clustering methods have been described. Second, the k-means algorithm and its advantages and disadvantages are introduced. Then the Iris dataset is used to specify the k-means algorithm. A taxonomy of clustering algorithms and complexity of several algorithms are listed in the end.
Keywords :
Algorithm design and analysis; Classification algorithms; Clustering algorithms; Clustering methods; Complexity theory; Data mining; Databases; cluster algorithm; data mining; k-means; kdd; knime;
Conference_Titel :
E -Business and E -Government (ICEE), 2011 International Conference on
Conference_Location :
Shanghai, China
Print_ISBN :
978-1-4244-8691-5
DOI :
10.1109/ICEBEG.2011.5881902
