Geometric Divide and Conquer Classification for High-dimensional Data.
Pei Ling LaiYang Jin LiangAlfred InselbergPublished in: DATA (2012)
Keyphrases
- high dimensional data
- high dimensionality
- dimension reduction
- dimensionality reduction
- high dimensional
- small sample size
- low dimensional
- nearest neighbor
- data points
- data sets
- high dimensions
- regression problems
- data analysis
- subspace clustering
- similarity search
- support vector machine
- data distribution
- image classification
- missing values
- high dimensional spaces
- pattern recognition
- clustering high dimensional data
- machine learning
- input space
- sample size
- feature extraction
- input data
- multivariate temporal data
- feature selection
- high dimensional feature spaces
- original data
- text classification
- text data
- feature space
- classification algorithm
- subspace learning
- dimensional data
- training set
- manifold learning
- model selection
- linear discriminant analysis
- feature vectors
- decision trees
- high dimensional data sets
- variable weighting
- training samples