An Industrial Internet of Things Feature Selection Method Based on Potential Entropy Evaluation Criteria
In recent years, with the rapid development of industrial Internet of Things, the rapid growth of data has become a severe challenge and precious opportunity faced by many industries. The information society has entered the era of big data. Feature selection is frequently used to reduce the number o...
Main Authors: | Long Zhao, Xiangjun Dong |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8276556/ |
Similar Items
-
Feasibility of atrial fibrillation detection from a novel wearable armband device
by: Syed Khairul Bashar, MS, et al.
Published: (2021-06-01) -
Detecting Unfavorable Driving States in Electroencephalography Based on a PCA Sample Entropy Feature and Multiple Classification Algorithms
by: Tao Zhang, et al.
Published: (2020-11-01) -
Comparison of Feature Selection Techniques in Knowledge Discovery Process
by: Dijana Oreski, et al.
Published: (2014-11-01) -
Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection
by: Jaesung Lee, et al.
Published: (2016-11-01) -
Improved Measures of Redundancy and Relevance for mRMR Feature Selection
by: Insik Jo, et al.
Published: (2019-05-01)