Dimensionality reduction approaches and evolving challenges in high dimensional data.
Adnan UllahUsman QamarFarhan Hassan KhanSaba BashirPublished in: IML (2017)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- high dimensionality
- high dimensional
- dimensionality reduction methods
- manifold learning
- data points
- high dimensions
- data sets
- principal component analysis
- dimension reduction
- linear discriminant analysis
- nearest neighbor
- lower dimensional
- input space
- nonlinear dimensionality reduction
- dimensional data
- similarity search
- subspace clustering
- high dimensional spaces
- subspace learning
- principal components
- high dimensional datasets
- low rank
- data analysis
- original data
- euclidean distance
- sparse representation
- pattern recognition
- neural network
- data representation
- feature space
- real world
- high dimensional data sets
- clustering high dimensional data
- database
- small sample size