Nonlinear dimensionality reduction of mass spectrometry data for odor sensing.
Yuji NozakiTakamichi NakamotoPublished in: MFI (2015)
Keyphrases
- nonlinear dimensionality reduction
- mass spectrometry data
- pattern classification
- manifold learning
- high throughput
- low dimensional
- dimensionality reduction
- high dimensional data
- mass spectrometry
- cancer classification
- dimensionality reduction methods
- data acquisition
- riemannian manifolds
- pattern recognition
- locally linear embedding
- high dimensional
- data sets
- dimension reduction
- principal component analysis
- d objects