Fault Diagnosis Method of Joint Fisher Discriminant Analysis Based on the Local and Global Manifold Learning and Its Kernel Version.
Jian FengJian WangHuaguang ZhangZhiyan HanPublished in: IEEE Trans Autom. Sci. Eng. (2016)
Keyphrases
- manifold learning
- fisher discriminant analysis
- kernel trick
- dimensionality reduction
- locality preserving projections
- locality preserving
- feature space
- low dimensional
- nonlinear dimensionality reduction
- discriminant analysis
- multiple kernel learning
- dimensionality reduction methods
- high dimensional
- input space
- kernel methods
- high dimensional data
- subspace learning
- feature extraction
- principal component analysis
- semi supervised
- dimension reduction
- kernel function
- embedding space
- locally linear embedding
- support vector
- geodesic distance
- face recognition
- kernel pca
- manifold structure
- regression algorithm
- factor analysis
- riemannian manifolds
- kernel learning
- random projections
- data sets
- machine learning
- high dimensional feature space
- principle component analysis
- linear discriminant analysis
- sparse representation