Hybrid Feature Selection for High-Dimensional Manufacturing Data

Mapping Intimacies ◽

10.1109/etfa45728.2021.9613547 ◽

2021 ◽

Author(s):

Yajuan Sun ◽

Jianlin Yu ◽

Xiang Li ◽

Ji Yan Wu ◽

Wen Feng Lu

Keyword(s):

Feature Selection ◽

High Dimensional ◽

Selection For ◽

Manufacturing Data

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Data-driven Feature Selection for Long Longitudinal Breadth and High Dimensional Dataset

Proceedings of the 2020 12th International Conference on Machine Learning and Computing ◽

10.1145/3383972.3383992 ◽

2020 ◽

Author(s):

Ji-Han Liu ◽

Cheng-Tse Wu ◽

Ta-Wei Chu ◽

and Jyh-Shing Roger Jang

Keyword(s):

Feature Selection ◽

Data Driven ◽

High Dimensional ◽

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Incorporating genetic algorithm into rough feature selection for high dimensional biomedical data

2011 IEEE International Symposium on IT in Medicine and Education ◽

10.1109/itime.2011.6132040 ◽

2011 ◽

Author(s):

Vinh Quoc Dang ◽

Chiou-Peng Lam ◽

Chang Su Lee

Keyword(s):

Genetic Algorithm ◽

Feature Selection ◽

High Dimensional ◽

Biomedical Data ◽

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Feature selection for high-dimensional classification using a competitive swarm optimizer

Soft Computing ◽

10.1007/s00500-016-2385-6 ◽

2016 ◽

Vol 22 (3) ◽

pp. 811-822 ◽

Author(s):

Shenkai Gu ◽

Ran Cheng ◽

Yaochu Jin

Keyword(s):

Feature Selection ◽

High Dimensional ◽

Dimensional Classification ◽

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Improved Nonnegative Matrix Factorization Based Feature Selection for High Dimensional Data Analysis

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) ◽

10.2991/iccsee.2013.583 ◽

2013 ◽

Author(s):

Lincheng Jiang ◽

Wentang Tan ◽

Zhenwen Wang ◽

Fengjing Yin ◽

Bin Ge ◽

...

Keyword(s):

Feature Selection ◽

Data Analysis ◽

Matrix Factorization ◽

Nonnegative Matrix Factorization ◽

High Dimensional Data ◽

Nonnegative Matrix ◽

High Dimensional ◽

High Dimensional Data Analysis ◽

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Dynamic Feature Selection for Clustering High Dimensional Data Streams

IEEE Access ◽

10.1109/access.2019.2932308 ◽

2019 ◽

Vol 7 ◽

pp. 127128-127140 ◽

Author(s):

Conor Fahy ◽

Shengxiang Yang

Keyword(s):

Feature Selection ◽

Data Streams ◽

High Dimensional Data ◽

High Dimensional ◽

Dynamic Feature ◽

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Feature Selection for High-Dimensional Data — A Pearson Redundancy Based Filter

Advances in Soft Computing - Computer Recognition Systems 2 ◽

10.1007/978-3-540-75175-5_30 ◽

2007 ◽

pp. 242-249 ◽

Author(s):

Jacek Biesiada ◽

Wlodzisław Duch

Keyword(s):

Feature Selection ◽

High Dimensional Data ◽

High Dimensional ◽

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Feature Selection for High Dimensional Data Using Weighted K-Nearest Neighbors and Genetic Algorithm

IEEE Access ◽

10.1109/access.2020.3012768 ◽

2020 ◽

Vol 8 ◽

pp. 139512-139528

Author(s):

Shuangjie Li ◽

Kaixiang Zhang ◽

Qianru Chen ◽

Shuqin Wang ◽

Shaoqiang Zhang

Keyword(s):

Genetic Algorithm ◽

Feature Selection ◽

High Dimensional Data ◽

Nearest Neighbors ◽

High Dimensional ◽

K Nearest Neighbors ◽

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Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data

BMC Bioinformatics ◽

10.1186/s12859-020-3411-3 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Guang-Hui Fu ◽

Yuan-Jiao Wu ◽

Min-Jie Zong ◽

Jianxin Pan

Keyword(s):

Feature Selection ◽

Imbalanced Data ◽

Hellinger Distance ◽

High Dimensional ◽

Selection For ◽

Sparse Feature Selection

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High-dimensional feature selection for genomic datasets

Knowledge-Based Systems ◽

10.1016/j.knosys.2020.106370 ◽

2020 ◽

Vol 206 ◽

pp. 106370 ◽

Author(s):

Majid Afshar ◽

Hamid Usefi

Keyword(s):

Feature Selection ◽

High Dimensional ◽

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Neighborhood Component Feature Selection for High-Dimensional Data

Journal of Computers ◽

10.4304/jcp.7.1.161-168 ◽

2012 ◽

Vol 7 (1) ◽

Author(s):

Wei Yang ◽

Kuanquan Wang ◽

Wangmeng Zuo

Keyword(s):

Feature Selection ◽

High Dimensional Data ◽

High Dimensional ◽

Selection For ◽

Component Feature

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