A Hybrid Feature Selection Method RFSTL for Manufacturing Quality Prediction Based on a High Dimensional Imbalanced Dataset

A Hybrid Feature Selection Method RFSTL for Manufacturing Quality Prediction Based on a High Dimensional Imbalanced Dataset

Under Industry 4.0, manufacturing quality prediction has been gaining increased interest from researchers and manufacturers. From the analysis of previous studies on quality predictions using machine learning, it became clear that the high dimensionality and imbalance of data are major and common pr...

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Bibliographic Details
Main Authors: Hong Zhou, Kun-Ming Yu, Yen-Chiu Chen, Huan-Po Hsu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Imbalanced data
feature selection
quality prediction
Industry 40
random forest
fine Gaussian SVM
Online Access:https://ieeexplore.ieee.org/document/9354177/

Internet

https://ieeexplore.ieee.org/document/9354177/

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