In this study, we discuss the application of K-means clustering technique on classification of NBA guards, including determination category number, classification results analysis and evaluation about result. Based on the NBA data, using rebounds, assists and points as clustering factors to K-Means clustering analysis. We implement an improved K-Means clustering analysis for classification of NBA guards. Further experimental result shows that the best sample classification number is six according to the mean square error function evaluation. Depending on K-means clustering algorithm the final classification reflects an objective and comprehensive classification, objective evaluation for NBA guards.

[1] Jiawei Han. Data Mining Concepts and Techniques [M].Beijing: Mechanical Industry Press .2006.
[2] http://en.wikipedia.org/wiki/K-means_clustering.
[3] Liu Chang Qian. K-means algorithm improvements and network intrusion detection application [J]. Computer simulation .2011.
[4] Yan Xinge .ISODATA and fuzzy K-means algorithm applied in image segmentation [C]. Chinese Optical Society 2004 Academic Conference.
[5]Qu Xiaoning .K-means clustering algorithm in commercial banking customers classification [J]. Computer simulation .2011.
[6] Raymond T. Ng and Jiawei Han, CLARANS: A Method for Clustering Objects for Spatial Data Mining, IEEE TRANSACTIONS ONKNOWLEDGE and DATA ENGINEERING. 2002.
[7] Zhu Xian based on simulated annealing Particle Swarm Optimization techniques of genetic data biclustering research [M]. Nanjing Normal University .2009.
[8]Yin Z.D .Based collaborative filtering Trusted Service Selection [M]. Nanjing University of Posts and Telecommunications.2013.
[9] Jiangwen Rui. Distributed machine learning framework based on cloud [M]. Xiamen University .2013.
[10] Data Source: http: //www.stat-nba.com/.
[11] Sun Jigui, Liu Jie, Zhaolian Yu clustering algorithm [J] Journal of Software 2008.
[12] Jin Ming. Optimization Selection and Evaluation of Technical Index Classification of NBA Elite Guard of. China Sport Science and Technology. 2005.
[13] Richard J. Roiger, Michael W. Geatz, Data Mining a tutorial-based primer, Addison-Wesley, 2003.
[14] Josef Cihlar, Rasim Latifovic, Jean Beaubien. “A Comparison Of Clustering Strategies For Unsupervised Classification,” Canadian Journal of Remote Sensi.

@article{Libao05011001,
title = " Application of K-Means Clustering Algorithm for Classification of NBA Guards ",
journal = "International Journal of Science and Engineering Applications (IJSEA)",
volume = "5",
number = "1",
pages = "001 - 006",
year = "2016",
author = " Libao ZHANG,Faming LU,An LIU,Pingping GUO,Cong LIU ",
}