PCA-based high-dimensional noisy data clustering via control of decision errors.
Jeonghwa LeeChi-Hyuck JunPublished in: Knowl. Based Syst. (2013)
Keyphrases
- noisy data
- high dimensional
- high dimensionality
- noise tolerant
- data points
- class noise
- clustering algorithm
- k means
- clustering method
- principal component analysis
- dimensionality reduction
- missing data
- high dimensional data
- learning from noisy data
- decision rules
- low dimensional
- input data
- decision makers
- decision making
- missing values
- training data
- control system
- noise free
- high dimensional datasets
- high dimensional data sets
- data sets
- intrinsic dimensionality
- semi supervised
- cluster analysis
- image denoising
- multi dimensional
- similarity search