PBSVM: Partitioning and biased support vector machine for vocal fold pathology assessment using labeled and unlabeled data sets.
Tahereh Emami AzadiFarshad AlmasganjPublished in: Expert Syst. Appl. (2011)
Keyphrases
- training data
- support vector machine
- data sets
- training set
- unlabeled data
- supervised learning
- labeled data
- unlabeled training data
- labeled examples
- multi class
- test data
- support vector machine svm
- training samples
- semi supervised learning
- decision trees
- svm classifier
- class labels
- labeled training set
- decision boundary
- classification accuracy
- training examples
- text categorization
- high quality
- unlabeled documents
- real world
- active learning
- learning algorithm
- naive bayes
- feature selection
- prior knowledge
- database
- feature vectors
- decision forest
- real world data sets
- positive examples
- speech signal
- benchmark data sets
- radial basis function
- kernel methods
- classification method
- k nearest neighbor
- unsupervised learning
- semi supervised
- graph partitioning
- nearest neighbor
- high dimensional data
- text classification
- unseen data
- partitioning algorithm
- support vector
- multi class support vector machines