Robust and sparse k-means clustering for high-dimensional data.
Sárka BrodinováPeter FilzmoserThomas OrtnerChristian BreitenederMaia RohmPublished in: Adv. Data Anal. Classif. (2019)
Keyphrases
- high dimensional data
- high dimensional
- sparse representation
- low dimensional
- dimensionality reduction
- nearest neighbor
- high dimensions
- high dimensionality
- data points
- data analysis
- data sets
- subspace clustering
- similarity search
- clustering high dimensional data
- data distribution
- lower dimensional
- original data
- dimension reduction
- manifold learning
- high dimension
- linear discriminant analysis
- low rank
- high dimensional spaces
- dimensional data
- high dimensional datasets
- input space
- sparse coding
- high dimensional data sets
- high dimensional feature spaces
- image processing
- small sample size
- variable weighting
- clustering method
- input data
- multi dimensional
- computer vision