Deep ensemble forests for industrial fault classification.
Yue LiuZhiqiang GePublished in: IFAC J. Syst. Control. (2019)
Keyphrases
- training set
- classification accuracy
- pattern recognition
- random forests
- feature selection
- final classification
- classification systems
- machine learning
- ensemble classification
- classification algorithm
- multiple classifier systems
- multiple classifiers
- ensemble classifier
- pattern classification
- image classification
- feature extraction
- support vector
- decision trees
- neural network
- classification rules
- majority voting
- support vector machine
- industrial applications
- supervised learning
- feature vectors
- fault detection
- concept drifting data streams
- industrial processes
- preprocessing
- classifier ensemble
- expert systems
- regression problems
- supervised classification
- random forest
- ensemble methods
- cost sensitive
- fuzzy logic
- cross validation
- fault diagnosis
- prediction accuracy
- text classification