A Diagnostic Feature Subset Selection of Breast Tumor Based on Neighborhood Rough Set Model

Journal of the Korea Industrial Information Systems Research ◽

10.9723/jksiis.2016.21.6.013 ◽

2016 ◽

Vol 21 (6) ◽

pp. 13-21

Author(s):

Chang-Sik Son ◽

Rock-Hyun Choi ◽

Won-Seok Kang ◽

Jong-Ha Lee

Keyword(s):

Rough Set ◽

Breast Tumor ◽

Subset Selection ◽

Feature Subset Selection ◽

Diagnostic Feature ◽

Feature Subset ◽

Neighborhood Rough Set ◽

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Feature Subset Selection of Semi-supervised Data: An Intuitionistic Fuzzy-Rough Set-Based Concept

Advances in Intelligent Systems and Computing - Proceedings of International Ethical Hacking Conference 2018 ◽

10.1007/978-981-13-1544-2_25 ◽

2018 ◽

pp. 303-315 ◽

Author(s):

Shivam Shreevastava ◽

Anoop Tiwari ◽

Tanmoy Som

Keyword(s):

Rough Set ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Fuzzy Rough Set ◽

Intuitionistic Fuzzy ◽

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Neighborhood rough set based heterogeneous feature subset selection

Information Sciences ◽

10.1016/j.ins.2008.05.024 ◽

2008 ◽

Vol 178 (18) ◽

pp. 3577-3594 ◽

Author(s):

Qinghua Hu ◽

Daren Yu ◽

Jinfu Liu ◽

Congxin Wu

Keyword(s):

Rough Set ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Neighborhood Rough Set ◽

Heterogeneous Feature

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A Study on Feature Subset Selection Using Rough Set Theory

Journal of Advanced Mathematics and Applications ◽

10.1166/jama.2012.1018 ◽

2012 ◽

Vol 1 (2) ◽

pp. 239-249

Author(s):

Jianchao Han

Keyword(s):

Rough Set ◽

Rough Set Theory ◽

Subset Selection ◽

Feature Subset Selection ◽

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Rough Set-Based Feature Subset Selection Technique Using Jaccard’s Similarity Index

Advances in Intelligent Systems and Computing - Proceedings of International Ethical Hacking Conference 2018 ◽

10.1007/978-981-13-1544-2_39 ◽

2018 ◽

pp. 477-487

Author(s):

Bhawna Tibrewal ◽

Gargi Sur Chaudhury ◽

Sanjay Chakraborty ◽

Animesh Kairi

Keyword(s):

Rough Set ◽

Similarity Index ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Selection Technique ◽

Jaccard's Similarity Index

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Feature subset selection approach based on fuzzy rough set for high-dimensional data

2014 IEEE International Conference on Granular Computing (GrC) ◽

10.1109/grc.2014.6982810 ◽

2014 ◽

Author(s):

Changyou Guo ◽

Xuefeng Zheng

Keyword(s):

Rough Set ◽

High Dimensional Data ◽

Subset Selection ◽

Feature Subset Selection ◽

High Dimensional ◽

Feature Subset ◽

Fuzzy Rough Set ◽

Selection Approach

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Rough-Set-Inspired Feature Subset Selection, Classifier Construction, and Rule Aggregation

Rough Sets and Knowledge Technology - Lecture Notes in Computer Science ◽

10.1007/978-3-642-24425-4_13 ◽

2011 ◽

pp. 81-88 ◽

Author(s):

Dominik Ślęzak ◽

Sebastian Widz

Keyword(s):

Rough Set ◽

Subset Selection ◽

Feature Subset Selection ◽

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A hybrid genetic algorithm for feature subset selection in rough set theory

Soft Computing ◽

10.1007/s00500-013-1150-3 ◽

2013 ◽

Vol 18 (7) ◽

pp. 1373-1382 ◽

Author(s):

Si-Yuan Jing

Keyword(s):

Genetic Algorithm ◽

Rough Set ◽

Rough Set Theory ◽

Hybrid Genetic Algorithm ◽

Subset Selection ◽

Feature Subset Selection ◽

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Empirical evaluation of feature subset selection based on a real-world data set

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2004.03.005 ◽

2004 ◽

Vol 17 (3) ◽

pp. 285-288 ◽

Author(s):

Petra Perner ◽

Chid Apte

Keyword(s):

Empirical Evaluation ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Real World Data ◽

Data Set ◽

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Threshold accepting trained principal component neural network and feature subset selection: Application to bankruptcy prediction in banks

Applied Soft Computing ◽

10.1016/j.asoc.2007.12.003 ◽

2008 ◽

Vol 8 (4) ◽

pp. 1539-1548 ◽

Author(s):

V. Ravi ◽

C. Pramodh

Keyword(s):

Neural Network ◽

Subset Selection ◽

Principal Component ◽

Bankruptcy Prediction ◽

Feature Subset Selection ◽

Feature Subset ◽

Threshold Accepting

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Interaction between feature subset selection techniques and machine learning classifiers for detecting unsolicited emails

ACM SIGAPP Applied Computing Review ◽

10.1145/2600617.2600622 ◽

2014 ◽

Vol 14 (1) ◽

pp. 53-61 ◽

Author(s):

Shrawan Kumar Trivedi ◽

Shubhamoy Dey

Keyword(s):

Machine Learning ◽

Subset Selection ◽

Feature Subset Selection ◽

Feature Subset ◽

Machine Learning Classifiers ◽

Learning Classifiers

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