Classification of high dimensional data using LASSO ensembles.
Daniel UrdaLeonardo FrancoJosé M. JerezPublished in: SSCI (2017)
Keyphrases
- high dimensional data
- high dimensionality
- dimension reduction
- dimensionality reduction
- low dimensional
- high dimensional
- variable selection
- feature selection
- decision trees
- sparse representation
- nearest neighbor
- data sets
- data points
- subspace clustering
- small sample size
- regression problems
- similarity search
- high dimensional datasets
- cross validation
- high dimensions
- pattern recognition
- support vector
- high dimensional feature spaces
- clustering high dimensional data
- multivariate temporal data
- text classification
- feature vectors
- high dimensional spaces
- model selection
- image classification
- feature space
- manifold learning
- training samples
- machine learning
- lower dimensional
- data analysis
- low rank
- training set
- linear discriminant analysis
- classification algorithm
- support vector machine
- variable weighting
- feature extraction
- input data
- dimensional data
- support vector machine svm
- high dimensional data sets
- class labels
- locally linear embedding
- subspace learning
- input space
- linear regression
- euclidean distance
- sample size
- semi supervised
- neural network