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|Title:||Augmented nomogram with dependent feature pairs||Authors:||FU QIANG||Keywords:||Nomogram,visulization,dependencies,dependent feature pairs,Bayesian Network,feature selection||Issue Date:||12-Apr-2012||Citation:||FU QIANG (2012-04-12). Augmented nomogram with dependent feature pairs. ScholarBank@NUS Repository.||Abstract:||Nomogram is a method of visualizing the quantified contribution of a feature based on certain classifier. However, the original nomograms do not explicitly consider the joint effects of the dependent feature pairs. This thesis introduces the augmented nomogram with dependent feature pairs. An entropy-based method is firstly employed to discover the dependent feature pairs, a Bayesian Network is constructed to approximate the probability. Then this approximation is visualized using an augmented nomogram thereby enabling people to obtain the probability taking into account the effects of dependent features. A feature selection method is also proposed that utilizes the augmented nomogram whereby features are selected according to the range of quantified contribution in the nomogram. Experiment results show that the augmented nomogram generally outperforms existing non-augmented nomogram. The features selected by the augmented nomograms with dependent features outperform features selected using some state-of-the-art feature selection methods.||URI:||http://scholarbank.nus.edu.sg/handle/10635/35224|
|Appears in Collections:||Master's Theses (Open)|
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