Feature Selection for Support Vector Machine in the Study of Financial Early Warning System

Jingxiang Li; Yichen Qin; Danhui Yi; Yang Li; Ye Shen

doi:10.1002/qre.1684

Feature Selection for Support Vector Machine in the Study of Financial Early Warning System

Quality and Reliability Engineering International ◽

10.1002/qre.1684 ◽

2014 ◽

Vol 30 (6) ◽

pp. 867-877 ◽

Cited By ~ 4

Author(s):

Jingxiang Li ◽

Yichen Qin ◽

Danhui Yi ◽

Yang Li ◽

Ye Shen

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

Early Warning ◽

Early Warning System ◽

Warning System ◽

Support Vector ◽

Selection For

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Clinical Nursing Risk Assessment and Early Warning System based on Support Vector Machine

2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) ◽

10.1109/iaai51705.2020.9332816 ◽

2020 ◽

Author(s):

Tong Men ◽

Ya-Hui Zhou

Keyword(s):

Risk Assessment ◽

Support Vector Machine ◽

Early Warning ◽

Early Warning System ◽

Warning System ◽

Support Vector ◽

Clinical Nursing

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Using support vector machine to develop an early warning system for the risks of derivative financial instruments

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) ◽

10.1109/fskd.2011.6019566 ◽

2011 ◽

Author(s):

Jie Zhang ◽

Yue-yao Sun

Keyword(s):

Support Vector Machine ◽

Early Warning ◽

Early Warning System ◽

Warning System ◽

Support Vector ◽

Financial Instruments

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Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph14030249 ◽

2017 ◽

Vol 14 (3) ◽

pp. 249 ◽

Cited By ~ 14

Author(s):

Jianzhou Wang ◽

Tong Niu ◽

Rui Wang

Keyword(s):

Support Vector Machine ◽

Air Quality ◽

Least Squares ◽

Early Warning ◽

Early Warning System ◽

Cloud Model ◽

Warning System ◽

Support Vector

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Usefulness of support vector machine to develop an early warning system for financial crisis

Expert Systems with Applications ◽

10.1016/j.eswa.2010.08.085 ◽

2011 ◽

Vol 38 (4) ◽

pp. 2966-2973 ◽

Cited By ~ 19

Author(s):

Jae Joon Ahn ◽

Kyong Joo Oh ◽

Tae Yoon Kim ◽

Dong Ha Kim

Keyword(s):

Support Vector Machine ◽

Financial Crisis ◽

Early Warning ◽

Early Warning System ◽

Warning System ◽

Support Vector

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Application of Fuzzy Entropy to Improve Feature Selection for Defect Recognition Using Support Vector Machine in High Voltage Cable Joints

IEEE Transactions on Dielectrics and Electrical Insulation ◽

10.1109/tdei.2020.009055 ◽

2020 ◽

Vol 27 (6) ◽

pp. 2147-2155

Author(s):

Chien-Kuo Chang ◽

Bharath Kumar Boyanapalli ◽

Ruay-Nan Wu

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

High Voltage ◽

Fuzzy Entropy ◽

Support Vector ◽

Selection For ◽

Defect Recognition

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Hybrid Deep-Readout Echo State Network and Support Vector Machine with Feature Selection for Human Activity Recognition

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Big Data Technologies and Applications ◽

10.1007/978-3-030-72802-1_11 ◽

2021 ◽

pp. 150-167

Author(s):

Shadi Abudalfa ◽

Kevin Bouchard

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

Activity Recognition ◽

Human Activity ◽

Human Activity Recognition ◽

Support Vector ◽

Echo State Network ◽

Selection For

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Differential evolution-based parameters optimisation and feature selection for support vector machine

International Journal of Computational Science and Engineering ◽

10.1504/ijcse.2016.10001039 ◽

2016 ◽

Vol 13 (4) ◽

pp. 355

Author(s):

Bo Li ◽

Lixin Ding ◽

Jun Li

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

Differential Evolution ◽

Support Vector ◽

Selection For

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Feature selection for support vector machine in financial crisis prediction: a case study in China

Expert Systems ◽

10.1111/j.1468-0394.2010.00546.x ◽

2010 ◽

Vol 27 (4) ◽

pp. 299-310 ◽

Cited By ~ 12

Author(s):

Xinping Song ◽

Yongsheng Ding ◽

Jingwen Huang ◽

Yan Ge

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

Financial Crisis ◽

Support Vector ◽

Selection For

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Analyzing the Performance of Intrusion Detection Model Using Weighted One-Against-One Support Vector Machine and Feature Selection for Imbalanced Classes

International Journal of Intelligent Engineering and Systems ◽

10.22266/ijies2020.0430.15 ◽

2020 ◽

Vol 13 (2) ◽

pp. 151-160 ◽

Cited By ~ 1

Author(s):

Bambang Setiawan ◽

◽

Supeno Djanali ◽

Tohari Ahmad ◽

◽

...

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

Intrusion Detection ◽

Support Vector ◽

Detection Model ◽

Selection For ◽

Imbalanced Classes

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A Novel Method of Nonlinear Rapid Feature Selection for High Dimensional Data and Its Application in Peptide QSAR Modeling Based on Support Vector Machine

Acta Physico-Chimica Sinica ◽

10.3866/pku.whxb20110735 ◽

2011 ◽

Vol 27 (07) ◽

pp. 1654-1660 ◽

Cited By ~ 3

Author(s):

DAI Zhi-Jun ◽

◽

ZHOU Wei ◽

YUAN Zhe-Ming ◽

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

High Dimensional Data ◽

High Dimensional ◽

Support Vector ◽

Qsar Modeling ◽

Novel Method ◽

Selection For

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