Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data.
Minh Tuan DoanJianzhong QiSutharshan RajasegararChristopher LeckiePublished in: IEEE BigData (2018)
Keyphrases
- subspace clustering
- high dimensional data
- high dimensional
- dimensionality reduction
- subspace clusters
- low dimensional
- nearest neighbor
- high dimensionality
- clustering high dimensional data
- similarity search
- original data
- dimension reduction
- data sets
- data points
- complex data
- data analysis
- manifold learning
- high dimensional spaces
- tree structure
- decision trees
- dimensional data
- high dimensional feature spaces
- input space
- lower dimensional
- high dimensional datasets
- neural network
- subspace projections
- text data
- metric space
- input data
- clustering method