An improved mixture of probabilistic PCA for nonlinear data-driven process monitoring.
Jingxin ZhangHao ChenSonghang ChenXia HongPublished in: CoRR (2020)
Keyphrases
- data driven
- principal component analysis
- kernel pca
- principal components analysis
- face recognition
- feature extraction
- principal components
- linear dimensionality reduction
- kernel principal component analysis
- mixture model
- probabilistic model
- dimensionality reduction
- high dimensional
- bayesian networks
- covariance matrix
- independent component analysis
- source separation
- latent variable models
- generalized em algorithm
- uncertain data
- dimension reduction
- face images
- k means
- linear discriminant analysis
- kernel methods
- principle component analysis
- feature space