Utilization of Attribute Clustering Methods for Scalable Computation of Reducts from High-Dimensional Data.
Andrzej JanuszDominik SlezakPublished in: FedCSIS (2012)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- nearest neighbor
- high dimensional
- high dimensionality
- data analysis
- subspace clustering
- decision table
- data sets
- high dimensions
- dimension reduction
- rough sets
- manifold learning
- original data
- attribute reduction
- nonlinear dimensionality reduction
- data points
- input space
- data distribution
- sparse representation
- similarity search
- subspace learning
- decision rules
- missing values
- attribute values
- clustering high dimensional data
- high dimensional datasets
- high dimensional spaces
- linear discriminant analysis
- high dimensional data sets
- text data
- variable selection
- rough set theory
- principal component analysis
- neural network
- dimensional data
- feature selection
- condition attributes