Doubly supervised embedding based on class labels and intrinsic clusters for high-dimensional data visualization.
Hannah KimJaegul ChooChandan K. ReddyHaesun ParkPublished in: Neurocomputing (2015)
Keyphrases
- data visualization
- class labels
- input space
- high dimensional
- supervised learning
- data points
- cluster structure
- label information
- labeled data
- output space
- data analysis
- unlabeled data
- semi supervised
- nonlinear dimensionality reduction
- data samples
- visual data mining
- training data
- training set
- high dimensional data
- data mining
- unsupervised learning
- multi label
- clustering algorithm
- learning algorithm
- knowledge discovery
- training examples
- big data
- dimensionality reduction
- low dimensional
- feature set
- feature space
- databases
- vector space
- active learning
- cluster analysis
- multiple types
- multi dimensional
- manifold learning
- data clustering
- data distribution
- feature selection
- semi supervised learning
- text classification