A Projection Pursuit framework for supervised dimension reduction of high dimensional small sample datasets.
Soledad EspezuaEdwin VillanuevaCarlos Dias MacielAndré C. P. L. F. de CarvalhoPublished in: Neurocomputing (2015)
Keyphrases
- dimension reduction
- high dimensional
- small sample
- high dimensionality
- high dimensional problems
- low dimensional
- feature selection
- high dimensional data
- principal component analysis
- variable selection
- feature extraction
- dimensionality reduction
- sparse metric learning
- machine learning
- unsupervised learning
- pattern recognition
- manifold learning
- data points
- sample size
- data sets
- supervised learning
- semi supervised
- singular value decomposition
- image segmentation
- bayesian framework
- decision trees
- neural network