Unsupervised Locality-Preserving Robust Latent Low-Rank Recovery-Based Subspace Clustering for Fault Diagnosis.
Jie GaoMyeongsu KangJing TianLifeng WuMichael G. PechtPublished in: IEEE Access (2018)
Keyphrases
- fault diagnosis
- low rank
- subspace clustering
- high dimensional data
- manifold structure
- dimensionality reduction
- neural network
- high dimensional
- semi supervised
- low dimensional
- manifold learning
- convex optimization
- missing data
- data sets
- clustering method
- matrix factorization
- clustering algorithm
- data analysis
- nearest neighbor
- linear combination
- data points
- high dimensionality
- singular value decomposition
- high order
- unsupervised learning
- linear discriminant analysis
- similarity search
- supervised learning
- original data
- latent variables
- pairwise
- latent space
- random projections
- data mining
- machine learning
- pattern recognition
- text mining