Dimensionality reduction using MCE-optimized LDA transformation.
Xiao-Bing LiJin-Yu LiRen-Hua WangPublished in: ICASSP (1) (2004)
Keyphrases
- dimensionality reduction
- linear discriminant analysis
- principal component analysis
- high dimensional
- low dimensional
- pattern recognition
- high dimensional data
- feature extraction
- latent dirichlet allocation
- dimension reduction
- manifold learning
- discriminant analysis
- data points
- data representation
- dimensionality reduction methods
- feature space
- principal components
- high dimensionality
- subspace learning
- lower dimensional
- nonlinear dimensionality reduction
- face recognition
- linear dimensionality reduction
- pattern recognition and machine learning
- supervised dimensionality reduction
- random projections
- singular value decomposition
- multidimensional scaling
- generative model
- data analysis
- dealing with high dimensional data
- locally linear embedding
- principle component analysis
- scatter matrices
- hidden markov models
- feature selection
- discriminant projection