The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering.
Marco SaerensFrançois FoussLuh YenPierre DupontPublished in: ECML (2004)
Keyphrases
- spectral clustering
- principal components analysis
- graph laplacian
- graph partitioning
- laplacian matrix
- graph construction
- normalized cut
- graph clustering
- similarity matrix
- label propagation
- covariance matrix
- similarity graph
- spectral methods
- data clustering
- pairwise
- clustering method
- dimensionality reduction
- affinity matrix
- principal components
- feature extraction
- clustering algorithm
- image segmentation
- constrained spectral clustering
- bipartite graph
- multivariate statistical analysis
- graph representation
- weighted graph
- linear discriminant analysis
- random walk
- k means
- graph model
- principal component analysis
- computer vision
- graph kernels
- data sets
- text classification
- lower bound