Feature Selection of Power Quality Disturbance Signals with an Entropy-Importance-Based Random Forest.
Nantian HuangGuobo LuGuowei CaiDianguo XuJiafeng XuFuqing LiLiying ZhangPublished in: Entropy (2016)
Keyphrases
- random forest
- power quality disturbance
- decision trees
- feature selection
- selected features
- feature set
- naive bayes
- fold cross validation
- feature ranking
- signal processing
- classification models
- wavelet transform
- machine learning
- lifting wavelet
- ensemble methods
- text classification
- text categorization
- machine learning algorithms
- ensemble classifier
- feature extraction
- base classifiers
- classification accuracy
- training set
- feature space
- high resolution
- k nearest neighbor
- support vector
- data sets
- image processing
- power quality
- multiscale
- cost sensitive
- feature vectors
- image classification
- active learning