Selecting Examples in Manifold Reduced Feature Space for Active Learning.
Catarina SilvaBernardete RibeiroPublished in: ICMLA (2008)
Keyphrases
- feature space
- active learning
- training examples
- low dimensional
- high dimensional
- training set
- high dimensionality
- mean shift
- high dimension
- feature vectors
- lower dimensional
- labeled examples
- training samples
- input space
- riemannian manifolds
- manifold learning
- semi supervised
- dimensionality reduction
- data points
- feature extraction
- kernel function
- feature selection
- machine learning
- random sampling
- cost sensitive
- learning algorithm
- dimension reduction
- learning strategies
- principal component analysis
- relevance feedback
- kernel methods
- feature set
- supervised learning
- euclidean space
- dissimilarity measure
- support vector machine
- knn
- kernel pca
- learning process
- image retrieval
- embedding space