An Efficient Estimation and Classification Methods for High Dimensional Data Using Robust Iteratively Reweighted SIMPLS Algorithm Based on nu-Support Vector Regression.
Abdullah Mohammed RashidHabshah MidiWaleed DhhanJayanthi ArasanPublished in: IEEE Access (2021)
Keyphrases
- high dimensional data
- support vector classification
- support vector regression
- preprocessing
- support vector machine svm
- regression model
- high dimensionality
- support vector
- regression problems
- subspace clustering
- input data
- high dimensional spaces
- high dimensional
- cross validation
- detection algorithm
- learning algorithm
- dimensional data
- pattern recognition
- nearest neighbor
- dimension reduction
- locally linear embedding
- machine learning
- simulated annealing
- data sets
- k means
- data analysis
- dimensionality reduction
- high dimensional datasets
- decision trees
- low dimensional structure
- low dimensional
- hybrid ga
- high dimensional data sets
- computer vision
- feature space
- training set
- feature vectors
- input space
- manifold learning
- data points
- support vector machine
- feature set
- kernel function