Title :
Missing Data Treatment Methods and NBI Model
Author :
Liu, Peng ; Lei, Lei
Author_Institution :
Sch. of Inf. Manage. & Eng., Shanghai Univ. of Finance & Econ.
Abstract :
After reviewing missing mechanism, methods classification, and several well known treatment methods for missing data handling, this paper proposes a new method NBI, Naive Bayesian Imputation. NBI models use the imputation attribute as class attribute to build NBC. In this way, the imputation problem is turned into classification problem. NBC is insensitive to missing data and can be improved by attribute selection strategy. Extensive experiments on datasets from UCI are conducted to assess the effectiveness of NBI
Keywords :
Bayes methods; data handling; pattern classification; NBI model; Naive Bayesian Imputation models; classification problem; methods classification; missing data handling; missing data treatment; Bayesian methods; Classification algorithms; Data engineering; Data handling; Data mining; Finance; Information management; Niobium compounds; Training data; Waste materials;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.194
