Accuracy of Different Machine Learning Type Methodologies for EEG Classification by Diagnosis.
Andrius Vytautas Misiukas MisiunasTadas MeskauskasRuta SamaitienePublished in: NMA (2018)
Keyphrases
- machine learning
- classification accuracy
- pattern recognition
- decision trees
- supervised learning
- accuracy rate
- machine learning algorithms
- machine learning methods
- text classification
- supervised machine learning
- data mining
- roc analysis
- feature selection
- training set
- predictive accuracy
- eeg signals
- artificial intelligence
- feature space
- support vector machine
- classification method
- classification algorithm
- classification rate
- information extraction
- unsupervised learning
- image classification
- feature extraction
- fold cross validation
- induction algorithms
- prediction accuracy
- eeg data
- supervised classification
- breast cancer diagnosis
- medical diagnosis
- inductive learning
- pattern classification
- fault diagnosis
- neural network
- high accuracy
- support vector
- training data
- learning algorithm
- generalization ability
- support vector machine svm
- frequency band
- multiple classifier systems
- feature vectors
- cancer diagnosis
- event related
- learning methodologies