Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data.
Minh Tuan DoanJianzhong QiSutharshan RajasegararChristopher LeckiePublished in: CoRR (2018)
Keyphrases
- subspace clustering
- high dimensional data
- dimensionality reduction
- nearest neighbor
- subspace clusters
- high dimensional
- high dimensionality
- low dimensional
- clustering high dimensional data
- data sets
- data analysis
- data points
- manifold learning
- similarity search
- original data
- decision trees
- input space
- dimensional data
- dimension reduction
- subspace clustering algorithms
- high dimensional spaces
- high dimensional feature spaces
- subspace projections
- complex data
- linear discriminant analysis
- lower dimensional
- tree structure
- input data
- data structure
- feature selection
- computer vision
- machine learning