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Classification by Weighting, Similarity and kNN

Intelligent Data Engineering and Automated Learning – IDEAL 2006, 2006, p.57-64

2006

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Combining multiple K-nearest neighbor classifiers for text classification by reducts

Lecture notes in computer science, 2002, p.340-347

2002

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Classification by Instance-Based Learning Algorithm

Intelligent Data Engineering and Automated Learning - IDEAL 2005, 2005, p.133-140

2005

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An Efficient Method for Computing All Reducts

Transactions of the Japanese Society for Artificial Intelligence, 2004, Vol.19(3), pp.166-173

2004

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Partition for the rough set-based text classification

Lecture notes in computer science, 2003, p.181-188

2003

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Combining Feature Selection with Feature Weighting for k-NN Classifier

Intelligent Data Engineering and Automated Learning — IDEAL 2002, 2002, p.461-468

2002

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Mapping of nearest neighbor for classification

2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS), 2013, p.121-126

2013

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Classification by Rough Set Reducts, AdaBoost and SVM

2010 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2010, p.63-68

2010

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Combining Multiple k-Nearest Neighbor Classifiers Using Different Distance Functions

Intelligent Data Engineering and Automated Learning – IDEAL 2004, 2004, p.634-641

2004

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Classification by Partil Data of Multiple Reducts-kNN with Confidence

2010 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010, Vol.1, p.94-101

2010

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Text Classification: Combining Grouping, LSA and kNN vs Support Vector Machine

Knowledge-Based Intelligent Information and Engineering Systems, 2006, p.393-400

2006

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Power Customer Credit Analysis and Decision Making Using Tolerant Rough Sets Model

2009 International Conference on Information Management, Innovation Management and Industrial Engineering, 2009, Vol.4, p.515-518

2009

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Classification by Multiple Reducts-kNN with Confidence

Intelligent Data Engineering and Automated Learning – IDEAL 2010, p.94-101

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Control of Variables in Reducts - kNN Classification with Confidence

Knowledge-Based and Intelligent Information and Engineering Systems, p.98-107

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Nearest Neighbor Classification by Relearning

Intelligent Data Engineering and Automated Learning - IDEAL 2009, p.42-49

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Text Classification by Combining Grouping, LSA and kNN

5th IEEE/ACIS International Conference on Computer and Information Science and 1st IEEE/ACIS International Workshop on Component-Based Software Engineering,Software Architecture and Reuse (ICIS-COMSAR'06), 2006, p.148-154

2006

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Modified Reducts and Their Processing for Nearest Neighbor Classification

Intelligent Data Engineering and Automated Learning - IDEAL 2012, p.753-762

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Generating representative from clusters of association rules on numeric attributes

Lecture notes in computer science, 2003, p.605-613

2003

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ON SIMULTANEOUS APPROXIMATION TO A DIFFERENTIABLE FUNCTION AND ITS DERIVATIVE BY INVERSE PAL-TYPE INTERPOLATION POLYNOMIALS

Approximation theory and its applications, 1995-12, Vol.11 (4), p.15-23

Yongguang, Bao

1995

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A Hybrid Method of Feature Subset Selection

Journal of Japan Society for Fuzzy Theory and Systems, 2002/12/15, Vol.14(6), pp.648-655

2002

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An effective Rough set-based method for text classification

Lecture notes in computer science, 2003, p.545-552

2003

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Improving performance of the k-nearest neighbor classifier by tolerant rough sets

Proceedings of the Third International Symposium on Cooperative Database Systems for Advanced Applications. CODAS 2001, 2001, p.167-171

2001

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Improving Performance of the k-Nearest Neighbor Classifier by Combining Feature Selection with Feature Weighting

Transactions of the Japanese Society for Artificial Intelligence, 2002, Vol.17(3), pp.209-216

2002

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Modified Reduct: Nearest Neighbor Classification

2012 IEEE/ACIS 11th International Conference on Computer and Information Science, 2012, p.310-315

2012

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Rough Set Based Learning for Classification

2008 20th IEEE International Conference on Tools with Artificial Intelligence, 2008, Vol.2, p.97-104

2008

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Classification by Weighting, Similarity and kNN

Combining multiple K-nearest neighbor classifiers for text classification by reducts

Classification by Instance-Based Learning Algorithm

An Efficient Method for Computing All Reducts

Partition for the rough set-based text classification

Combining Feature Selection with Feature Weighting for k-NN Classifier

Mapping of nearest neighbor for classification

Classification by Rough Set Reducts, AdaBoost and SVM

Combining Multiple k-Nearest Neighbor Classifiers Using Different Distance Functions

Classification by Partil Data of Multiple Reducts-kNN with Confidence

Text Classification: Combining Grouping, LSA and kNN vs Support Vector Machine

Power Customer Credit Analysis and Decision Making Using Tolerant Rough Sets Model

Classification by Multiple Reducts-kNN with Confidence

Control of Variables in Reducts - kNN Classification with Confidence

Nearest Neighbor Classification by Relearning

Text Classification by Combining Grouping, LSA and kNN

Modified Reducts and Their Processing for Nearest Neighbor Classification

Generating representative from clusters of association rules on numeric attributes

ON SIMULTANEOUS APPROXIMATION TO A DIFFERENTIABLE FUNCTION AND ITS DERIVATIVE BY INVERSE PAL-TYPE INTERPOLATION POLYNOMIALS

A Hybrid Method of Feature Subset Selection

An effective Rough set-based method for text classification

Improving performance of the k-nearest neighbor classifier by tolerant rough sets

Improving Performance of the k-Nearest Neighbor Classifier by Combining Feature Selection with Feature Weighting

Modified Reduct: Nearest Neighbor Classification

Rough Set Based Learning for Classification

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