Explaining Outliers by Subspace Separability.
Barbora MicenkováRaymond T. NgXuan-Hong DangIra AssentPublished in: ICDM (2013)
Keyphrases
- semi supervised
- subspace learning
- dimensionality reduction
- low rank representation
- data points
- outlier detection
- low dimensional
- principal component analysis
- feature space
- high dimensional
- high dimensional data
- missing data
- subspace clusters
- lower dimensional
- linear subspace
- robust statistics
- principal components analysis
- clustering high dimensional data
- robust statistical
- input data
- generating explanations
- probabilistic principal component analysis
- class separability
- subspace methods
- subspace clustering
- measurement error
- novelty detection
- grassmann manifold
- noisy data
- sparse representation
- outlier removal
- feature extraction
- data mining