Surface and intracranial EEG spike detection based on discrete wavelet decomposition and random forest classification.
Jean-Eudes Le DougetAmal FouadMohamed Maskani FilaliJan PyrzowskiMichel Le Van QuyenPublished in: EMBC (2017)
Keyphrases
- random forest
- wavelet decomposition
- decision trees
- feature set
- fold cross validation
- random forests
- feature vectors
- wavelet transform
- multiresolution
- classification accuracy
- decision tree learning algorithms
- feature extraction
- ensemble classifier
- subband
- eeg signals
- machine learning
- wavelet domain
- high frequency
- support vector machine
- feature selection
- supervised learning
- feature space
- multiscale
- data sets
- eeg data
- support vector machine svm
- wavelet coefficients
- sar images
- support vector
- base classifiers
- image segmentation
- training data
- brain computer interface
- ensemble methods
- multi class
- text classification
- image classification