Hybrid Dimensionality Reduction Forest With Pruning for High-Dimensional Data Classification.
Weihong ChenYuhong XuZhiwen YuWenming CaoC. L. Philip ChenGuoqiang HanPublished in: IEEE Access (2020)
Keyphrases
- high dimensional data
- dimensionality reduction
- high dimensionality
- dimension reduction
- low dimensional
- dimensionality reduction methods
- pattern recognition
- feature space
- high dimensional
- feature extraction
- nearest neighbor
- nonlinear dimensionality reduction
- subspace clustering
- small sample size
- linear discriminant analysis
- feature selection
- high dimensions
- similarity search
- principal component analysis
- data sets
- data points
- original data
- subspace learning
- lower dimensional
- input space
- high dimensional feature spaces
- manifold learning
- supervised dimensionality reduction
- high dimensional spaces
- data analysis
- decision trees
- diffusion maps
- clustering high dimensional data
- dimensional data
- feature vectors
- input data
- kernel learning
- neural network
- euclidean distance
- class labels
- text classification
- support vector
- random projections
- principal components analysis
- principal components
- locally linear embedding
- multi dimensional
- feature set
- high dimensional data sets
- training set
- machine learning
- data mining
- variable weighting