Clustered Discriminant Regression for High-Dimensional Data Feature Extraction and Its Applications in Healthcare and Additive Manufacturing.
Bo ShenWeijun XieZhenyu James KongPublished in: IEEE Trans Autom. Sci. Eng. (2021)
Keyphrases
- high dimensional data
- feature extraction
- dimensionality reduction
- regression problems
- low dimensional
- principal component analysis
- discriminant analysis
- linear discriminant analysis
- dimension reduction
- manifold learning
- high dimensional
- high dimensionality
- input space
- nearest neighbor
- feature space
- locality preserving projections
- regression model
- similarity search
- high dimensions
- data sets
- data points
- subspace clustering
- data analysis
- face recognition
- feature vectors
- dimensional data
- lower dimensional
- sparse representation
- pattern recognition
- image processing
- variable selection
- dimensionality reduction methods
- high dimensional datasets
- linear regression
- low rank
- support vector machine svm
- data mining
- subspace learning
- high dimensional spaces
- feature set
- face images
- knn
- small sample size
- feature selection
- model selection
- input data
- multi dimensional
- high dimensional data sets
- clustering high dimensional data