Locally Linear Embedding for dimensionality reduction in QSAR.
Pierre-Jean L'HeureuxJulie CarreauYoshua BengioOlivier DelalleauShi Yi YuePublished in: J. Comput. Aided Mol. Des. (2004)
Keyphrases
- locally linear embedding
- dimensionality reduction
- nonlinear dimensionality reduction
- dimensional reduction
- manifold learning
- low dimensional
- high dimensional data
- high dimensional
- laplacian eigenmaps
- principal component analysis
- dimensionality reduction methods
- linear discriminant analysis
- subspace learning
- pattern recognition
- data representation
- diffusion maps
- principal components
- feature extraction
- feature selection
- principal components analysis
- high dimensionality
- locality preserving projections
- data points
- preprocessing step
- random projections
- feature space
- dimensional data
- neighborhood preserving embedding
- underlying manifold
- dimension reduction
- euclidean distance
- neural network
- data sets
- metric learning
- singular value decomposition
- semi supervised
- data analysis
- data structure
- data mining