Feature subset selection for support vector machines using confident margin

Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. ◽

10.1109/ijcnn.2005.1555973 ◽

2006 ◽

Author(s):

M. Kugler ◽

K. Aoki ◽

S. Kuroyanagi ◽

A. Iwata ◽

A.S. Nugroho

Keyword(s):

Support Vector Machines ◽

Subset Selection ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

Vector Machines ◽

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Feature subset selection for support vector machines by incremental regularized risk minimization

2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541) ◽

10.1109/ijcnn.2004.1380930 ◽

2005 ◽

Author(s):

H. Frohlich ◽

A. Zell

Keyword(s):

Support Vector Machines ◽

Subset Selection ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

Risk Minimization ◽

Vector Machines ◽

Selection For ◽

Regularized Risk Minimization

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Feature Subset Selection for Support Vector Machines Through Discriminative Function Pruning Analysis

IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) ◽

10.1109/tsmcb.2002.805808 ◽

2004 ◽

Vol 34 (1) ◽

pp. 60-67 ◽

Author(s):

K.Z. Mao

Keyword(s):

Support Vector Machines ◽

Subset Selection ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

Vector Machines ◽

Discriminative Function ◽

Selection For ◽

Pruning Analysis

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Feature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector Machines

Journal of Computer Science ◽

10.3844/jcssp.2011.707.714 ◽

2011 ◽

Vol 7 (5) ◽

pp. 707-714 ◽

Author(s):

Johnson

Keyword(s):

Genetic Algorithm ◽

Support Vector Machines ◽

Subset Selection ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

Vector Machines ◽

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Feature subset selection for support vector machines through sensitivity analysis

Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826) ◽

10.1109/icmlc.2004.1384586 ◽

2005 ◽

Author(s):

De-Feng Wang ◽

P.P.K. Chan ◽

D.S. Yeung ◽

E.C.C. Tsang

Keyword(s):

Sensitivity Analysis ◽

Support Vector Machines ◽

Subset Selection ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

Vector Machines ◽

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Fisher score and Matthews correlation coefficient-based feature subset selection for heart disease diagnosis using support vector machines

Knowledge and Information Systems ◽

10.1007/s10115-018-1185-y ◽

2018 ◽

Vol 58 (1) ◽

pp. 139-167 ◽

Author(s):

Syed Muhammad Saqlain ◽

Muhammad Sher ◽

Faiz Ali Shah ◽

Imran Khan ◽

Muhammad Usman Ashraf ◽

...

Keyword(s):

Matthews Correlation Coefficient ◽

Subset Selection ◽

Disease Diagnosis ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

Fisher Score ◽

Vector Machines ◽

Selection For ◽

Heart Disease Diagnosis

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Kernel Construction and Feature Subset Selection in Support Vector Machines

Lecture Notes in Computer Science - Simulated Evolution and Learning ◽

10.1007/978-3-319-68759-9_49 ◽

2017 ◽

pp. 605-616

Author(s):

Shinichi Yamada ◽

Kourosh Neshatian

Keyword(s):

Support Vector Machines ◽

Subset Selection ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

Vector Machines

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Variable Subset Selection for Credit Scoring with Support Vector Machines

Operations Research Proceedings - Operations Research Proceedings 2005 ◽

10.1007/3-540-32539-5_40 ◽

2006 ◽

pp. 251-256 ◽

Author(s):

Ralf Stecking ◽

Klaus B. Schebesch

Keyword(s):

Support Vector Machines ◽

Credit Scoring ◽

Subset Selection ◽

Support Vector ◽

Vector Machines ◽

Selection For ◽

Variable Subset Selection ◽

Variable Subset

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Feature Subset Selection for Support Vector Machine Through Separability Assessment in Kernel-Defined Feature Space

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2007.2434 ◽

2007 ◽

Vol 4 (7) ◽

pp. 1417-1425

Author(s):

Yaohua Tang ◽

Jinghuai Gao ◽

Cunxiang Yang ◽

Xiaoliang Yang

Keyword(s):

Support Vector Machine ◽

Subset Selection ◽

Feature Space ◽

Feature Subset Selection ◽

Support Vector ◽

Feature Subset ◽

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Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory

The 2010 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2010.5596450 ◽

2010 ◽

Author(s):

Davide Anguita ◽

Alessandro Ghio ◽

Noemi Greco ◽

Luca Oneto ◽

Sandro Ridella

Keyword(s):

Machine Learning ◽

Support Vector Machines ◽

Model Selection ◽

Learning Theory ◽

Support Vector ◽

Advantages And Disadvantages ◽

Vector Machines ◽

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A PSO-Based Feature Subset Selection for Application of Spam /Non-spam Detection

Soft Computing Applications and Intelligent Systems - Communications in Computer and Information Science ◽

10.1007/978-3-642-40567-9_16 ◽

2013 ◽

pp. 183-193 ◽

Author(s):

Amir Rajabi Behjat ◽

Aida Mustapha ◽

Hossein Nezamabadi-pour ◽

Md. Nasir Sulaiman ◽

Norwati Mustapha

Keyword(s):

Subset Selection ◽

Feature Subset Selection ◽

Spam Detection ◽

Feature Subset ◽

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