Classification of Fatigue Bill Based on Support Vector Machine by Using Acoustic Signal.
Dongshik KangMasaki HigaNobuo ShojiMasanobu FujitaIkugo MitsuiPublished in: IWANN (2) (2009)
Keyphrases
- support vector machine
- acoustic signal
- acoustic signals
- svm classifier
- classification method
- support vector
- feature vectors
- support vector machine svm
- classification algorithm
- decision boundary
- svm classification
- machine learning
- small sample
- training set
- multi class
- model selection
- pattern recognition
- high classification accuracy
- supervised classification
- classification accuracy
- feature space
- decision trees
- feature selection
- pattern classification
- classification systems
- cross validation
- classification scheme
- classification process
- majority voting
- soft margin
- classification models
- neural network
- benchmark datasets
- supervised learning
- feature extraction
- automatic classification
- generalization ability
- hyperplane
- decision rules
- image classification
- nearest neighbor
- training data
- multi class support vector machines