Supervised dimension reduction for ordinal predictors.
Liliana ForzaniRodrigo García ArancibiaPamela LlopDiego TomassiPublished in: Comput. Stat. Data Anal. (2018)
Keyphrases
- dimension reduction
- unsupervised learning
- feature selection
- feature extraction
- principal component analysis
- high dimensional problems
- singular value decomposition
- semi supervised
- high dimensional
- learning algorithm
- manifold learning
- low dimensional
- supervised learning
- random projections
- variable selection
- high dimensionality
- cluster analysis
- linear discriminant analysis
- partial least squares
- high dimensional data
- feature space
- data mining and machine learning
- high dimensional data analysis
- discriminative information
- manifold embedding
- preprocessing
- feature subspace
- dimension reduction methods
- data mining
- sparse metric learning
- dimensionality reduction
- computer vision
- machine learning