Nonlinear feature selection based on hybrid KCCA-FNN algorithm for modeling

2011 International Conference on Business Management and Electronic Information ◽

10.1109/icbmei.2011.5920958 ◽

2011 ◽

Author(s):

Jun Yi ◽

Taifu Li ◽

Su Yingying ◽

Hu Wenjin ◽

Gao Ting

Keyword(s):

Feature Selection ◽

Nonlinear Feature

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Nonlinear Feature Selection with the Potential Support Vector Machine

Feature Extraction - Studies in Fuzziness and Soft Computing ◽

10.1007/978-3-540-35488-8_20 ◽

2008 ◽

pp. 419-438 ◽

Author(s):

Sepp Hochreiter ◽

Klaus Obermayer

Keyword(s):

Support Vector Machine ◽

Feature Selection ◽

Support Vector ◽

Nonlinear Feature

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Subspace detection based on the combination of nonlinear feature extraction and feature selection

2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) ◽

10.1109/whispers.2013.8080632 ◽

2013 ◽

Author(s):

Md. Ali Hossain ◽

Xiuping Jia ◽

Mark Pickering

Keyword(s):

Feature Extraction ◽

Feature Selection ◽

Subspace Detection ◽

Nonlinear Feature Extraction ◽

Nonlinear Feature

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A Hybrid Model Based on ANFIS and Nonlinear Feature Selection for Credit Risk Evaluation

DEStech Transactions on Social Science Education and Human Science ◽

10.12783/dtssehs/emass2018/20398 ◽

2018 ◽

Author(s):

Zhi-bin XIONG

Keyword(s):

Feature Selection ◽

Credit Risk ◽

Hybrid Model ◽

Risk Evaluation ◽

Model Based ◽

Selection For ◽

Nonlinear Feature

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Kernel-OPBS Algorithm: A Nonlinear Feature Selection Method for Hyperspectral Imagery

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2019.2924972 ◽

2020 ◽

Vol 17 (3) ◽

pp. 464-468

Author(s):

Xiaorun Li ◽

Wenqiang Zhang ◽

Shengda Niu ◽

Zhiyu Cao ◽

Liaoying Zhao

Keyword(s):

Feature Selection ◽

Hyperspectral Imagery ◽

Feature Selection Method ◽

Selection Method ◽

Nonlinear Feature

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Pixels of chemical structures correlate to chromatographic detector responses using genetic algorithm-adaptive neuro-fuzzy inference system as a novel nonlinear feature selection method

Chemometrics and Intelligent Laboratory Systems ◽

10.1016/j.chemolab.2020.104032 ◽

2020 ◽

Vol 202 ◽

pp. 104032

Author(s):

Nasser Jalili-Jahani ◽

Ehsan Zeraatkar ◽

Azadeh Fatehi ◽

Marsa Gholamian

Keyword(s):

Genetic Algorithm ◽

Feature Selection ◽

Fuzzy Inference System ◽

Fuzzy Inference ◽

Feature Selection Method ◽

Selection Method ◽

Inference System ◽

Chemical Structures ◽

Neuro Fuzzy ◽

Nonlinear Feature

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Nonlinear feature selection using Gaussian kernel SVM-RFE for fault diagnosis

Applied Intelligence ◽

10.1007/s10489-018-1140-3 ◽

2018 ◽

Vol 48 (10) ◽

pp. 3306-3331 ◽

Author(s):

Yangtao Xue ◽

Li Zhang ◽

Bangjun Wang ◽

Zhao Zhang ◽

Fanzhang Li

Keyword(s):

Feature Selection ◽

Fault Diagnosis ◽

Gaussian Kernel ◽

Nonlinear Feature ◽

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A hybrid fuzzy time series model based on ANFIS and integrated nonlinear feature selection method for forecasting stock

Neurocomputing ◽

10.1016/j.neucom.2016.03.068 ◽

2016 ◽

Vol 205 ◽

pp. 264-273 ◽

Author(s):

Chung-Ho Su ◽

Ching-Hsue Cheng

Keyword(s):

Time Series ◽

Feature Selection ◽

Feature Selection Method ◽

Selection Method ◽

Time Series Model ◽

Fuzzy Time Series ◽

Model Based ◽

Nonlinear Feature

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Nonlinear Feature Selection by Relevance Feature Vector Machine

Machine Learning and Data Mining in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/978-3-540-73499-4_12 ◽

2007 ◽

pp. 144-159 ◽

Author(s):

Haibin Cheng ◽

Haifeng Chen ◽

Guofei Jiang ◽

Kenji Yoshihira

Keyword(s):

Feature Selection ◽

Feature Vector ◽

Nonlinear Feature

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A mixed classification approach for the prediction of Parkinson's disease using nonlinear feature selection technique based on the voice recording

2017 International Conference on Inventive Computing and Informatics (ICICI) ◽

10.1109/icici.2017.8365279 ◽

2017 ◽

Author(s):

Satyabrata Aich ◽

Mangal Sain ◽

Jinse Park ◽

Ki-Won Choi ◽

Hee-Cheol Kim

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Feature Selection ◽

Feature Selection Technique ◽

Classification Approach ◽

Selection Technique ◽

Nonlinear Feature ◽

The Voice ◽

Voice Recording

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Incorporation of pre-classifier and nonlinear feature selection for tropical wood species recognition system

2015 10th Asian Control Conference (ASCC) ◽

10.1109/ascc.2015.7244484 ◽

2015 ◽

Author(s):

Imanurfatiehah Ibrahim ◽

Anis Salwa Mohd Khairuddin ◽

Rubiyah Yusof

Keyword(s):

Feature Selection ◽

Wood Species ◽

Species Recognition ◽

Recognition System ◽

Tropical Wood ◽

Selection For ◽

Nonlinear Feature

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