Tree-based mining contrast subspace

International Journal of Advances in Intelligent Informatics

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Field Value
 
Title Tree-based mining contrast subspace
 
Creator Sia, Florence
Alfred, Rayner
 
Subject
 
Description All existing mining contrast subspace methods employ density-based likelihood contrast scoring function to measure the likelihood of a query object to a target class against other class in a subspace. However, the density tends to decrease when the dimensionality of subspaces increases causes its bounds to identify inaccurate contrast subspaces for the given query object. This paper proposes a novel contrast subspace mining method that employs tree-based likelihood contrast scoring function which is not affected by the dimensionality of subspaces. The tree-based scoring measure recursively binary partitions the subspace space in the way that objects belong to the target class are grouped together and separated from objects belonging to other class. In contrast subspace, the query object should be in a group having a higher number of objects of the target class than other class. It incorporates the feature selection approach to find a subset of one-dimensional subspaces with high likelihood contrast score with respect to the query object. Therefore, the contrast subspaces are then searched through the selected subset of one-dimensional subspaces. An experiment is conducted to evaluate the effectiveness of the tree-based method in terms of classification accuracy. The experiment results show that the proposed method has higher classification accuracy and outperform the existing method on several real-world data sets.
 
Publisher Universitas Ahmad Dahlan
 
Contributor
 
Date 2019-07-23
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/359
10.26555/ijain.v5i2.359
 
Source International Journal of Advances in Intelligent Informatics; Vol 5, No 2 (2019): July 2019; 169-178
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/359/ijain_v5i2_p169-178
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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