Results 221 to 230 of about 619 (257)

The method of attribute reduction based on discernibility matrix

2010 International Conference on Computer Application and System Modeling (ICCASM 2010), 2010
With respect to decision table, especially the inconsistent ones. On the basis of equivalent partitions, This paper quantifies the elements in the same class deduced by condition attribute belonging to different decision attribute classes, generates the discernibility matrix and measures the indexes of attribute significance reasonable, and then uses ...
null Lv Yue-jin, null Liu Hong-mei, null Jiang Jian-jun   +2 more
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Efficient Attribute Reduction Algorithm Based on Skowron Discernibility Matrix

2009 International Workshop on Intelligent Systems and Applications, 2009
The elements of discernibility matrix are used as the heuristic information by all the existing attribute reduction algorithms based on discernibility matrix. The time and space complexities of this kind of algorithms are O(\C\ 2 |U\ 2 ). To lower the time and space complexities, the simplified decision table and simplified discernibility matrix is ...
Zhangyan Xu, Liyu Huang, Bingru Yang
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Exhaustive Search with Belief Discernibility Matrix and Function

2013
This paper proposes a new feature selection method based on rough sets to take away the unnecessary attributes for the classification process from partially uncertain decision system. The uncertainty exists only in the decision attributes (classes) and is represented by the belief function theory.
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras   +2 more
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Discernibility Matrix-Based Attribute Reduction Algorithm of Decision Table

Advanced Materials Research, 2012
A discernibility matrix-based attribute reduction algorithm of decision table is introduced in this paper, which takes the importance of attributes as the heuristic message. This method solves the problem of the attribute selection when the frequencies of decision table attributes are equal.
Ying He, Dan He
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Dimensionality reduction of EEG signal using Fuzzy Discernibility Matrix

2017 10th International Conference on Human System Interactions (HSI), 2017
High dimensionality of feature space is a problem in supervised machine learning. Redundant or superfluous features either slow down the training process or dilute the quality of classification. Many methods are available in literature for dimensionality reduction.
Rajdeep Chatterjee, Tathagata Bandyopadhyay, Debarshi Kumar Sanyal, Dibyajyoti Guha   +3 more
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Heuristic for Attribute Selection Using Belief Discernibility Matrix

2012
This paper proposes a new heuristic attribute selection method based on rough sets to remove the superfluous attributes from partially uncertain data. We handle uncertainty only in decision attributes (classes) under the belief function framework.
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras   +2 more
openaire   +1 more source

The Improved Discernibility Matrix Based on Decision Vector

2013
Skowron’s discernibility matrix is the evolvement of the attribute reduction models under algebra view. Aiming at the generating process of discernibility matrix, this paper simplifies decision system by introducing decision vector, and designs an improved discernibility matrix, which is capable of suiting inconsistency of decision system, as well as ...
Jingfu Li, Denghui Bu
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A Feature Selection Algorithm Based on Discernibility Matrix

2007
A heuristic algorithm of reduct computation for feature selection is proposed in the paper, which is a discernibility matrix based method and aims at reducing the number of irrelevant and redundant features in data mining. The method used both significance information of attributes and information of discernibility matrix to define the necessity of ...
Fuyan Liu, Shaoyi Lu
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Incremental Target Recognition Algorithm Based on Improved Discernibility Matrix

2005
An incremental target recognition algorithm based on improved discernibility matrix in rough set theory is presented. Some comparable experiments have been completed in our “Information Fusion System for Communication Interception Information (IFS/CI2)”.
Liu Yong, Xu Congfu, Yan Zhiyong, Pan Yunhe   +3 more
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A Discernibility Matrix Based Algorithm for Feature Selection

2006 International Conference on Computational Intelligence and Security, 2006
An algorithm of reduct computation for feature selection is proposed in the paper, which is a discernibility matrix based method and aims at reducing the number of irrelevant and redundant features in data mining. The method used both significance information of attributes and information of discernibility matrix to define the necessity of heuristic ...
openaire   +1 more source