Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning.
Michel CrucianuDaniel EstevezVincent OriaJean-Philippe TarelPublished in: BDA (2007)
Keyphrases
- hyperplane
- feature space
- active learning
- input space
- training samples
- data points
- kernel function
- query processing
- kernel space
- linear classifiers
- range queries
- feature vectors
- linear separability
- similarity search
- support vector machine
- linearly separable
- maximal margin
- decision boundary
- separating hyperplane
- support vector
- training set
- similarity queries
- incremental learning algorithm
- feature selection
- index structure
- r tree
- high dimensional
- feature extraction
- convex hull
- database
- metric space
- neural network
- multi dimensional
- semi supervised
- low dimensional
- dimensionality reduction
- supervised learning
- relevance feedback
- learning process
- principal components
- training examples
- input data
- feature set
- nearest neighbor search
- image retrieval
- decision trees