Unlabeled Data Classification via Support Vector Machines and k-means Clustering.
Maokuan LiYusheng ChengHonghai ZhaoPublished in: CGIV (2004)
Keyphrases
- unlabeled data
- support vector
- labeled data
- co training
- class labels
- semi supervised classification
- semi supervised learning
- semi supervised
- labeled and unlabeled data
- supervised learning
- classification accuracy
- improve the classification accuracy
- text classification
- training set
- active learning
- supervised learning algorithms
- training data
- training examples
- support vector machine
- feature selection
- select relevant features
- semi supervised learning algorithms
- label information
- semisupervised learning
- labeled training data
- unlabeled samples
- labeled examples
- generalization ability
- svm classifier
- decision boundary
- labeled instances
- data points
- machine learning
- domain adaptation
- learning tasks
- learning problems
- naive bayes
- pairwise
- learning algorithm
- loss function
- machine learning algorithms
- document classification
- class distribution
- feature space
- support vector machine svm
- text categorization
- feature vectors
- decision trees
- supervised and semi supervised
- data sets
- clustering algorithm
- instance selection
- support vectors
- feature extraction
- object recognition
- kernel function
- prior knowledge
- unsupervised learning