BorderShift: toward optimal MeanShift vector for cluster boundary detection in high-dimensional data.
Xiaofeng CaoBaozhi QiuGuandong XuPublished in: Pattern Anal. Appl. (2019)
Keyphrases
- high dimensional data
- boundary detection
- subspace clustering
- mean shift
- data points
- high dimensional
- dimensionality reduction
- low dimensional
- nearest neighbor
- high dimensionality
- data sets
- clustering high dimensional data
- high dimensions
- similarity search
- original data
- variable weighting
- data analysis
- image segmentation
- data clustering
- detection algorithm
- dimension reduction
- dynamic programming
- text data
- berkeley segmentation dataset
- high dimensional spaces
- input space
- manifold learning
- linear discriminant analysis
- optimal solution
- feature space
- high dimensional datasets
- subspace clusters
- real world
- clustering algorithm
- feature selection
- nonlinear dimensionality reduction
- high dimensional data sets
- pairwise
- data mining