Partition of Discrete Numerical Interval Based on Local Outlier Coefficient Wave Method

Author

Zhang, Qiuyu ; Sun, Lei ; Zhen, Luning ; Jin, Yanfeng

Author_Institution

Coll. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou

fYear

2007

fDate

14-17 Sept. 2007

Firstpage

151

Lastpage

153

Abstract

The partition of discrete numerical interval is the foundation of discrete numerical data mining, and its research is significant in application. A new method for the partition of discrete numerical interval is proposed here. In the method the original samples are preprocessed, and then the local outlier coefficient of each data calculated. Eventually, the discrete numerical interval is partitioned by local outlier coefficient wave (LOCW), which keeps original distribution of data. The partitioned intervals have advantages of data aggregation in same interval and data sparsity between different intervals. The experiments demonstrate the validity of the proposed method.

Keywords

data mining; data aggregation; data mining; data sparsity; discrete numerical interval; local outlier coefficient wave method; Computer networks; Data analysis; Data mining; Educational institutions; Kernel; Lab-on-a-chip; Nearest neighbor searches; Postal services; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Bio-Inspired Computing: Theories and Applications, 2007. BIC-TA 2007. Second International Conference on

Conference_Location

Zhengzhou

Print_ISBN

978-1-4244-4105-1

Electronic_ISBN

978-1-4244-4106-8

Type

conf

DOI

10.1109/BICTA.2007.4806439

Filename

4806439