An Incomplete Data Classification Model Based on Relaxed Conservative Inference Rule
Ruihua Qi, Deli Yang · 2010
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.