How to solve classification and regression problems on high-dimensional data with a supervised extension of slow feature analysis.
Alberto N. EscalanteLaurenz WiskottPublished in: J. Mach. Learn. Res. (2013)
Keyphrases
- high dimensional data
- regression problems
- classification and regression problems
- dimensionality reduction
- high dimensional
- nearest neighbor
- low dimensional
- high dimensionality
- data sets
- subspace clustering
- data analysis
- input space
- data points
- manifold learning
- missing values
- high dimensional spaces
- clustering high dimensional data
- machine learning
- supervised learning
- feature selection
- learning algorithm
- genetic algorithm
- model selection
- k nearest neighbor
- unsupervised learning
- input data
- pattern recognition
- computer vision
- high dimensional datasets
- data mining
- neural network