Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA.
Benyamin GhojoghAli GhodsiFakhri KarrayMark CrowleyPublished in: AI (2022)
Keyphrases
- factor analysis
- locally linear embedding
- independent component analysis
- principal component analysis
- dimensionality reduction
- discriminant analysis
- principal components analysis
- low dimensional
- component analysis
- manifold learning
- dimensionality reduction methods
- high dimensional
- high dimensional data
- dimensional data
- linear discriminant analysis
- cluster analysis
- dimension reduction
- feature space
- statistical tests
- locality preserving projections
- multi dimensional
- probabilistic model
- feature extraction
- matrix factorization
- geodesic distance
- face recognition
- data representation
- principal components
- random projections
- subspace learning
- data mining
- covariance matrix
- pattern recognition