Attribute Clustering and Dimensionality Reduction Based on In/Out Degree of Attributes in Dependency Graph.
Asit Kumar DasJaya SilSantanu PhadikarPublished in: SEMCCO (1) (2011)
Keyphrases
- dependency graph
- dimensionality reduction
- attribute values
- high dimensional data
- data points
- high dimensionality
- numerical attributes
- unsupervised learning
- categorical attributes
- dependency graphs
- clustering algorithm
- categorical data
- pattern recognition and machine learning
- multiple attributes
- clustering method
- low dimensional
- structure preserving
- data clustering
- k means
- hierarchical clustering
- high dimensional
- data structure
- semantic attributes
- document clustering
- principal component analysis
- schema matching
- multidimensional scaling
- data representation
- multi attribute
- data objects
- visual attributes
- relevant attributes
- decision table
- manifold learning
- self organizing maps
- binary valued
- dealing with high dimensional data
- unsupervised feature selection
- numeric attributes
- nominal attributes
- data sets
- discernibility matrix
- nonlinear dimensionality reduction
- dimensionality reduction methods
- kernel learning
- principal components analysis
- numerical data
- fuzzy clustering
- spectral clustering
- pattern recognition
- feature extraction
- image processing