Projective ART with buffers for the high dimensional space clustering and an application to discover stock associations.
Lian LiuLihong HuangMingyong LaiChaoqun MaPublished in: Neurocomputing (2009)
Keyphrases
- high dimensional spaces
- high dimensional
- high dimensional data
- low dimensional
- high dimensionality
- nearest neighbor
- high dimensional datasets
- dimensionality reduction
- data points
- dimensional data
- low dimensional spaces
- high dimensional data sets
- multi dimensional
- feature space
- clustering method
- subspace clustering
- k means
- clustering algorithm
- similarity search
- lower dimensional
- higher dimensional
- outlier detection
- unsupervised learning
- spectral clustering
- input space
- cluster analysis
- data sets
- self organizing maps
- association rules
- planar curves
- hierarchical clustering
- manifold learning
- stock price
- distance metric
- feature selection
- neural network