Classification of arrhythmia disease through electrocardiogram signals using sampling vector random forest classifier.
S. Dhanunjay ReddyR. MuruganArnab NandiTripti GoelPublished in: Multim. Tools Appl. (2023)
Keyphrases
- heart rate variability
- ecg signals
- heart rate
- feature vectors
- pattern classification
- decision trees
- beat classification
- feature selection
- pattern recognition
- eeg signals
- spectral analysis
- classification algorithm
- text classification
- signal processing
- classification accuracy
- feature extraction
- supervised learning
- image classification
- atrial fibrillation
- biomedical signals
- classification scheme
- automatic classification
- support vector
- machine learning
- vector space
- classification method
- sample size
- benchmark datasets
- support vector machine svm
- support vector machine
- training set
- preprocessing
- svm classifier
- random sampling
- class labels
- multi class
- disease diagnosis
- electrical activity
- feature space
- data sets