Dimensionality Reduction by Locally Linear Discriminant Analysis for Handwritten Chinese Character Recognition.
Xue GaoJinzhi GuoLianwen JinPublished in: IEICE Trans. Inf. Syst. (2012)
Keyphrases
- linear discriminant analysis
- dimensionality reduction
- handwritten chinese character recognition
- discriminant analysis
- principal component analysis
- high dimensional data
- dimension reduction
- feature extraction
- high dimensional
- low dimensional
- small sample size
- feature space
- discriminant features
- pattern recognition
- manifold learning
- lower dimensional
- subspace learning
- data representation
- linear discriminant
- principal components analysis
- high dimensionality
- null space
- dealing with high dimensional data
- dimensionality reduction methods
- class separability
- random projections
- data points
- linear projection
- metric learning
- principal components
- face recognition
- feature selection
- subspace methods
- discriminative information
- class discrimination
- singular value decomposition
- discriminant projection
- novelty detection
- data sets
- locality preserving projections
- unsupervised feature selection
- scatter matrices
- knn
- supervised dimensionality reduction
- neural network