Classification by ensembles from random partitions of high-dimensional data.
Hongshik AhnHojin MoonMelissa J. FazzariNoha LimJames J. ChenRalph L. KodellPublished in: Comput. Stat. Data Anal. (2007)
Keyphrases
- high dimensional data
- high dimensionality
- dimension reduction
- high dimensional
- dimensionality reduction
- small sample size
- low dimensional
- nearest neighbor
- similarity search
- regression problems
- decision trees
- data sets
- subspace clustering
- data points
- feature space
- manifold learning
- data analysis
- feature extraction
- missing values
- high dimensions
- data distribution
- high dimensional feature spaces
- nonlinear dimensionality reduction
- feature selection
- input data
- clustering high dimensional data
- high dimensional datasets
- input space
- dimensional data
- sparse representation
- linear discriminant analysis
- pattern recognition
- support vector machine
- sample size
- high dimensional spaces
- text classification
- model selection
- variable selection
- support vector machine svm
- class labels
- classification algorithm
- training samples
- lower dimensional
- database
- feature set
- feature vectors
- high dimensional data sets
- machine learning
- data mining
- multivariate temporal data