Feature selection for support vector regression via Kernel penalization

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

10.1109/ijcnn.2010.5596488 ◽

2010 ◽

Author(s):

Sebastian Maldonado ◽

Richard Weber

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Support Vector ◽

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Feature selection for support vector regression using probabilistic prediction

Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '10 ◽

10.1145/1835804.1835849 ◽

2010 ◽

Author(s):

Jian-Bo Yang ◽

Chong-Jin Ong

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Support Vector ◽

Probabilistic Prediction ◽

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Combining support vector regression with feature selection for multivariate calibration

Neural Computing and Applications ◽

10.1007/s00521-008-0202-6 ◽

2008 ◽

Vol 18 (7) ◽

pp. 813-820 ◽

Author(s):

Guo-Zheng Li ◽

Hao-Hua Meng ◽

Mary Qu Yang ◽

Jack Y. Yang

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Multivariate Calibration ◽

Support Vector ◽

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Support Vector Regression with Feature Selection for the Multivariate Calibration of Spectrofluorimetric Determination of Aromatic Amino Acids

2007 IEEE 7th International Symposium on BioInformatics and BioEngineering ◽

10.1109/bibe.2007.4375658 ◽

2007 ◽

Author(s):

Guo-Zheng Li ◽

Hao-Hua Meng ◽

Mary Qu Yang ◽

Jack Y. Yang

Keyword(s):

Amino Acids ◽

Feature Selection ◽

Support Vector Regression ◽

Multivariate Calibration ◽

Aromatic Amino Acids ◽

Support Vector ◽

Spectrofluorimetric Determination ◽

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Feature selection for support vector regression in the application of building energy prediction

2011 IEEE 9th International Symposium on Applied Machine Intelligence and Informatics (SAMI) ◽

10.1109/sami.2011.5738878 ◽

2011 ◽

Author(s):

Hai-xiang Zhao ◽

Frederic Magoules

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Building Energy ◽

Support Vector ◽

Energy Prediction ◽

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Support Vector Regression Machine with Enhanced Feature Selection for Transient Stability Evaluation

2009 Asia-Pacific Power and Energy Engineering Conference ◽

10.1109/appeec.2009.4918854 ◽

2009 ◽

Author(s):

B. Dora Arul Selvi ◽

N. Kamaraj

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Transient Stability ◽

Support Vector ◽

Stability Evaluation ◽

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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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Review for "Improving Harris hawks optimization algorithm for hyperparameters estimation and feature selection in v‐support vector regression based on opposition‐based learning"

10.1002/cem.3311/v1/review2 ◽

2020 ◽

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Optimization Algorithm ◽

Support Vector ◽

Opposition Based Learning

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Feature Selection for Support Vector Machines in Financial Time Series Forecasting

Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents - Lecture Notes in Computer Science ◽

10.1007/3-540-44491-2_38 ◽

2000 ◽

pp. 268-273 ◽

Author(s):

L. J. Cao ◽

Francis E. H. Tay

Keyword(s):

Time Series ◽

Feature Selection ◽

Support Vector Machines ◽

Financial Time Series ◽

Time Series Forecasting ◽

Support Vector ◽

Financial Time ◽

Vector Machines ◽

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Forecasting wind speed using support vector regression and feature selection

2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech) ◽

10.1109/robomech.2017.8261144 ◽

2017 ◽

Author(s):

Nicolene Botha ◽

Christiaan M. van der Walt

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

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Feature Selection Method for L1-norm Twin Support Vector Regression

10.1109/iccais52680.2021.9624538 ◽

2021 ◽

Author(s):

Fan Wang ◽

Qing Wu ◽

Yanlin Fu

Keyword(s):

Feature Selection ◽

Support Vector Regression ◽

Feature Selection Method ◽

Selection Method ◽

Support Vector ◽

L1 Norm ◽

Twin Support Vector Regression

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