Results 41 to 50 of about 1,653,449 (187)
Neighbourhood systems based attribute reduction in formal decision contexts
CAAI Transactions on Intelligence Technology, 2019 Attribute reduction of formal decision context mainly uses the relationship between two concept lattices generated by the condition and decision attributes to remove redundant condition attributes.
Xiaohe Zhang +3 more
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, 2018 Attribute reduction is an important topic in the research of rough set theory, and it has been widely used in many aspects. Reduction based on an identifiable matrix is a common method, but a lot of space is occupied by repetitive and redundant ...
Weihua Xu, Xiaoyan Zhang, Jia Zhang
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An Improved Rough Clustering Using Discernibility Based Initial Seed Computation [PDF]
, 2010 In this paper, we present the discernibility approach for an initial seed computation of Rough K-Means (RKM). We propose the use of the discernibility initial seed computation (ISC) for RKM.
Djoko Budiyanto Setyohadi +5 more
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Attribute reduction based on maximal rules in decision formal context [PDF]
International Journal of Computational Intelligence Systems, 2014 One of the key issues in the theory of concept lattices is to extract the useful rules from the decision formal context. The maximal rules implicate the others, thus people are interested in them.
Leijun Li, Jusheng Mi, Bin Xie
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, 2015 In this work, we first define picture fuzzy soft sets and study some of their relevant properties, especially, a sufficient and necessary condition is presented to ensure that the dual laws are true in picture fuzzy soft theory.
Ji, Shiwei, +3 more
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Identity and Discernibility in Philosophy and Logic
, 2012 Questions about the relation between identity and discernibility are important both in philosophy and in model theory. We show how a philosophical question about identity and discernibility can be ‘factorized’ into a philosophical question about the ...
Pettigrew, R.G +2 more
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ATTRIBUTE VALUE PAIRS BASED ON DISCERNIBILITY MATRIX FOR OUTLIERS DETECTION
, 2022 Outlier mining is one important task in data mining and it has always been receiving attention from many researchers. The detection of outliers is found useful in many real applications like fraud detection and network intrusion.
UNIVERSITAS BINA DARMA, UNIVERSITAS BINA DARMA
core
The Method of Data Analysis in Intuitionistic Fuzzy Generalized Consistent Decision Formal Context
Entropy, 2019 Concept lattice has been successfully applied to various fields as an effective tool for data analysis and knowledge discovery, with attribute reduction being the key problem.
Binbin Sang +3 more
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Generalized Discernibility Function Based Attribute Reduction in Incomplete Decision Systems [PDF]
, 2013 A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table.
Dinh, Vu Van, Giang, Nguyen Long
core
A Variable Precision Attribute Reduction Approach in Multilabel Decision Tables
The Scientific World Journal, 2014 Owing to the high dimensionality of multilabel data, feature selection in multilabel learning will be necessary in order to reduce the redundant features and improve the performance of multilabel classification.
Hua Li +4 more
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