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Fuzzy rough relation
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The objective of the thesis: Proposes filter-wrapper algorithms for fuzzy rough set based attribute reduction in decision tables to reduce the cardinality of reduct and increase significantly the classification accuracy.
28p
extraenglish
24-05-2021
12
3
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The paper depicts complete study about the second method with some proposed algorithms. It focuses mainly on binary classification with kNN and SVM for imbalanced data. Experiments and comparisons among related methods will confirm pros and coin of each method with respect to performance accuracy and time consumption.
20p
viguam2711
11-01-2021
10
2
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The paper aims to improve the multi-label classification performance using the feature reduction technique. According to the determination of the dependency among features based on fuzzy rough relation, features with the highest dependency score will be retained in the reduction set.
8p
tamynhan4
06-09-2020
4
1
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In this paper, we propose a fuzzy distance based attribute reduction method on the decision table with numerical attribute value domain. Experiments on data sets show that the proposed method is more efficient than the ones based on Shannon’s entropy on the executed time and the classification accuracy of reduct.
9p
vitomato2711
11-03-2020
23
0
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