Selection of features and combination of classifiers using a fuzzy approach for acoustic event classification.
Andrey TemkoDusan MachoCliment NadeuPublished in: INTERSPEECH (2005)
Keyphrases
- feature set
- classification models
- svm classifier
- classification method
- classification decisions
- extracted features
- classification process
- class labels
- feature vectors
- classification accuracy
- feature extraction
- multiple classifiers
- classifier combination
- feature values
- classification algorithm
- final classification
- image classification
- feature subset
- decision trees
- decision tree classifiers
- machine learning approaches
- support vector machine classifiers
- support vector machine
- feature space
- feature selection algorithms
- support vector
- classification systems
- sequential forward selection
- classification rate
- machine learning methods
- pattern recognition
- training set
- feature weights
- multiple classifier systems
- supervised classification
- training samples
- feature selection
- training data
- bayesian classifier
- input features
- naive bayes
- support vector machine svm
- highly discriminative
- feature reduction
- multi category
- machine learning algorithms
- sufficient training data
- benchmark datasets
- naive bayes classifier
- binary classifiers
- majority voting
- combining classifiers
- multi class
- discriminative classifiers
- text classification
- image features
- multiple features
- roc curve
- classification performances
- train a support vector machine
- individual features
- linear svm
- bayes classifier
- single feature
- semi supervised
- training examples
- learning algorithm
- supervised learning
- probabilistic classifiers
- decision boundary
- fuzzy sets
- weak classifiers