Subspace Outlier Detection in High Dimensional Data using Ensemble of PCA-based Subspaces.
Mahboobeh Riahi-MadvarBabak NasersharifAhmad Akbari AziraniPublished in: CSICC (2021)
Keyphrases
- high dimensional data
- outlier detection
- low dimensional
- principal component analysis
- dimensionality reduction
- subspace clustering
- high dimensional datasets
- lower dimensional
- high dimensional
- nearest neighbor
- high dimensionality
- knowledge discovery
- similarity search
- detection algorithm
- data sets
- dimension reduction
- original data
- subspace clusters
- clustering high dimensional data
- data points
- input space
- detect outliers
- detecting outliers
- linear subspace
- low rank
- data streams
- neural network
- data mining
- subspace learning
- manifold learning
- principal components
- data analysis
- feature extraction
- dimensional data
- feature selection
- high dimensional spaces
- training set
- independent component analysis
- learning algorithm
- feature space
- face recognition
- training data
- pattern recognition
- euclidean distance
- real world
- least squares