Title :
Conditional Mutual Information Based Feature Selection
Author :
Cheng, Hongrong ; Qin, Zhiguang ; Qian, Weizhong ; Liu, Wei
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
In this paper, a new greedy feature selection algorithm is proposed to detect more precisely informative features. It overcomes the limitation of many existing MI-based gready feature selection algorithms. It is capable of detecting the relation of relevant feature combinations in some degree.In addition, the requirements of the memory storage and computation cost are low. Experimental results for the UCI benchmark dataset demonstrate the good performance of the proposed algorithm on the experimented data sets.
Keywords :
feature extraction; greedy algorithms; learning (artificial intelligence); pattern classification; conditional mutual information; feature detection; greedy feature selection algorithm; memory storage requirement; pattern classification; supervised learning; Accuracy; Boolean functions; Computational efficiency; Computer science; Filters; Knowledge acquisition; Knowledge engineering; Machine learning; Mutual information; Probability distribution; conditional mutual information; entropy; feature combination; feature selection;
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
DOI :
10.1109/KAM.2008.85
