Graph-guided Bayesian SVM with Adaptive Structured Shrinkage Prior for High-dimensional Data.
Wenli SunChanggee ChangQi LongPublished in: IEEE BigData (2021)
Keyphrases
- high dimensional data
- dimensionality reduction
- structured data
- low dimensional
- nearest neighbor
- high dimensional
- high dimensionality
- high dimensions
- support vector
- data points
- structured output
- data analysis
- data sets
- clustering high dimensional data
- knn
- support vector machine svm
- similarity search
- input space
- dimension reduction
- support vector machine
- subspace clustering
- high dimensional spaces
- data distribution
- manifold learning
- feature selection
- high dimensional datasets
- gaussian processes
- variable weighting
- linear discriminant analysis
- feature space
- weighted graph
- text data
- random walk
- lower dimensional
- pattern recognition
- nonlinear dimensionality reduction
- variable selection
- dimensional data
- input data
- feature vectors
- high dimensional data sets
- training data
- machine learning
- neural network