A Compressed PCA Subspace Method for Anomaly Detection in High-Dimensional Data.
Qi DingEric D. KolaczykPublished in: IEEE Trans. Inf. Theory (2013)
Keyphrases
- anomaly detection
- subspace methods
- high dimensional data
- linear discriminant analysis
- lower dimensional
- principal component analysis
- dimensionality reduction
- low dimensional
- high dimensional
- principal components analysis
- dimension reduction
- nearest neighbor
- data sets
- data points
- high dimensionality
- unsupervised learning
- subspace clustering
- principle component analysis
- linear subspace
- data analysis
- manifold learning
- sparse representation
- face recognition
- original data
- independent component analysis
- face databases
- random projections
- subspace learning
- neural network
- input data
- support vector machine
- hidden markov models
- dimensionality reduction methods