Aggregate features and ADABOOSTfor music classification.
James BergstraNorman CasagrandeDumitru ErhanDouglas EckBalázs KéglPublished in: Mach. Learn. (2006)
Keyphrases
- feature set
- feature extraction
- classification accuracy
- feature vectors
- classification process
- classification models
- svm classifier
- feature space
- automatic classification
- feature analysis
- classification method
- classification scheme
- feature values
- extracted features
- decision trees
- feature representation
- features extraction
- class labels
- discriminative features
- irrelevant features
- image classification
- genre classification
- preprocessing
- benchmark datasets
- classification algorithm
- support vector machine svm
- image features
- support vector machine
- machine learning
- extracting features
- feature extraction and classification
- low level
- music information retrieval
- feature construction
- svm classification
- pattern recognition
- feature weights
- audio features
- high dimensionality
- textural features
- music genre classification
- weak classifiers
- eeg signals
- feature selection algorithms
- data sets
- model selection
- supervised learning
- feature selection
- neural network