-Glycosylation by Support Vector Machines and Semi-supervised Learning.
Hirotaka SakamotoYukiko NakajimaKazutoshi SakakibaraMasahiro ItoIkuko NishikawaPublished in: ICONIP (1) (2008)
Keyphrases
- semi supervised learning
- support vector
- learning machines
- unlabeled data
- semi supervised
- labeled data
- learning problems
- supervised learning
- unsupervised learning
- machine learning
- active learning
- semi supervised classification
- co training
- label propagation
- training data
- training examples
- classification accuracy
- improve the classification accuracy
- kernel function
- graph based semi supervised learning
- manifold regularization
- semi supervised learning methods
- data sets
- support vector machine
- regularization framework
- transfer learning
- labeled and unlabeled data
- semi supervised learning algorithms
- support vectors
- learning models
- hyperplane
- kernel methods
- learning algorithm
- maximum margin
- metric learning
- graph construction
- multi view
- object recognition
- learning environment
- data mining