Exploring linear projections for revealing clusters, outliers, and trends in subsets of multi-dimensional datasets.
Jiazhi XiaLe GaoKezhi KongYing ZhaoYi ChenXiaoyan KuiYixiong LiangPublished in: J. Vis. Lang. Comput. (2018)
Keyphrases
- multi dimensional
- multi dimensional data
- data points
- high dimensional datasets
- outlier detection
- subspace clusters
- arbitrarily oriented
- clustering approaches
- three dimensional
- clustering algorithm
- subspace projections
- benchmark datasets
- synthetic datasets
- binary matrices
- fuzzy clustering
- data cube
- categorical attributes
- distance based outlier detection
- cluster structure
- subspace clustering
- hierarchical clustering
- noisy data
- cluster analysis
- high dimensional
- linear systems
- arbitrary shape
- database
- density based clustering
- fuzzy c means
- multiple dimensions
- dimensionality reduction
- data sets