Feature dimension reduction for microarray data analysis using locally linear embedding.
Chao ShiLihui ChenPublished in: APBC (2005)
Keyphrases
- dimension reduction
- locally linear embedding
- manifold learning
- microarray data analysis
- low dimensional
- high dimensional data
- high dimensional
- dimensionality reduction
- principal component analysis
- microarray data
- nonlinear dimensionality reduction
- manifold learning algorithm
- microarray
- locality preserving projections
- gene expression data
- feature extraction
- high dimensionality
- random projections
- feature selection
- cluster analysis
- linear discriminant analysis
- gene expression
- subspace learning
- partial least squares
- nearest neighbor
- feature space
- data points
- dimensionality reduction methods
- principal components
- unsupervised learning
- feature vectors
- principal components analysis
- singular value decomposition
- dimensional data
- preprocessing step
- similarity search
- feature set
- data sets
- multi dimensional
- manifold structure
- face recognition
- machine learning
- neural network