Adaptive dimension reduction for clustering high dimensional data.
Chris H. Q. DingXiaofeng HeHongyuan ZhaHorst D. SimonPublished in: ICDM (2002)
Keyphrases
- dimension reduction
- clustering high dimensional data
- high dimensional data
- high dimensional
- principal component analysis
- subspace clustering
- low dimensional
- high dimensionality
- dimensionality reduction
- feature extraction
- singular value decomposition
- high dimensional problems
- data mining and machine learning
- nearest neighbor
- feature selection
- manifold learning
- feature space
- partial least squares
- discriminative information
- high dimensional data analysis
- variable selection
- random projections
- dimension reduction methods
- cluster analysis
- pairwise
- data sets
- unsupervised learning
- preprocessing
- support vector machine
- decision trees
- sparse metric learning