Title :
An Incomplete Data Classification Model Based on Relaxed Conservative Inference Rule
Author :
Qi, Rui-hua ; Yang, De-li
Author_Institution :
Modern Educ. Technol. Center, Dalian Univ. of Foreign Language, Dalian, China
Abstract :
Aiming to increase the proportion of the samples that has been determinate classified in Naive Credal Classifier, this paper improves conservative inference rule and proposes an incomplete data classification model based on relaxed conservative inference rule. Simulation results of comparative experiment with Naive Bayesian Classifier and Naive Credal Classifier verify the effectiveness of this classification model.
Keywords :
data mining; inference mechanisms; pattern classification; incomplete data classification model; naive Bayesian classifier; naive Credal classifier; relaxed conservative inference rule; Accuracy; Classification algorithms; Data mining; Data models; Estimation; Robustness; Testing;
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
DOI :
10.1109/ICEEE.2010.5660793
