On the Number of Partial Least Squares Components in Dimension Reduction for Tumor Classification.
Xue-Qiang ZengGuo-Zheng LiGengfeng WuHua-Xing ZouPublished in: PAKDD Workshops (2007)
Keyphrases
- dimension reduction
- partial least squares
- principal component analysis
- feature extraction
- variable selection
- high dimensional data
- unsupervised learning
- discriminant analysis
- linear discriminant analysis
- singular value decomposition
- low dimensional
- dimensionality reduction
- feature selection
- high dimensional
- feature space
- machine learning
- high dimensionality
- image segmentation
- random projections