Arrhythmia Classification Based on Multiple Features Fusion and Random Forest Using ECG.
Zhizhong WangHongyi LiChuang HanSongwei WangLi ShiPublished in: J. Medical Imaging Health Informatics (2019)
Keyphrases
- multiple features
- random forest
- feature set
- decision trees
- feature fusion
- classification accuracy
- fold cross validation
- feature vectors
- feature space
- feature selection
- data fusion
- class labels
- heart rate variability
- feature extraction
- ecg signals
- classification models
- ensemble classifier
- mit bih arrhythmia database
- image classification
- beat classification
- incremental learning
- base classifiers
- support vector machine
- multi label
- combining multiple
- benchmark datasets
- training samples
- training set
- multi sensor
- fusion method
- svm classifier
- multiple instance learning
- metric learning
- information fusion
- information retrieval
- visual features
- multi class
- image retrieval
- support vector
- training data
- computer vision