Research on missing value estimation in data mining

Author

Feng, Deng-Chao ; Wang, Zhe ; Shi, Jian-Fang ; Pereira, J. M Dias

Author_Institution

Dept. of Electron. Eng., North China Inst. of Aerosp. Eng., Langfang

fYear

2008

fDate

25-27 June 2008

Firstpage

2048

Lastpage

2052

Abstract

Data missing in data pretreatment has a serious effect on the accuracy of subsequent analysis results in data mining. In this paper, the cause of data missing and the corresponding effect on data mining were discussed. Then the missing pattern and the application limitation of traditional missing value estimation were analyzed as well. Finally, the estimation algorithm of missing value in MAR (missing at random) pattern was mainly studied and applied in fault classification based on wavelet neural network. The experiment results show the efficiency of the algorithm.

Keywords

data mining; estimation theory; neural nets; pattern classification; wavelet transforms; data mining; data pretreatment; fault classification; missing value estimation; wavelet neural network; Algorithm design and analysis; Automation; Data analysis; Data engineering; Data mining; Intelligent control; Iterative algorithms; Neural networks; Pattern analysis; Probability; Data Mining; Expectation Maximization; Missing Value Estimation; Wavelet Neural Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-2113-8

Electronic_ISBN

978-1-4244-2114-5

Type

conf

DOI

10.1109/WCICA.2008.4593240

Filename

4593240