S-IAMB Algorithm for Markov Blanket Discovery
Zhang Yishi, Xu Hong, Yang Huang, Gangyi Qian · 2009
Using Markov Blanket for feature selection is one of important methods in machine learning. This paper analyses IAMB algorithm for discovering the Markov Blanket of a target variable from training data. Based on its characters and deficiency we introduce an improve algorithm of IAMB: SIAMB.The experimental results show that the S-IAMB algorithm performs better than IAMB by finding Markov Blanket of variables of ALARM dataset and by testing the performance with the classification tasks.