Description
- Introduction to high dimensional data
- Feature selection
- Feature extraction by linear methods
- Principal Component Analysis (PCA) & Kernel PCA
- Other linear transformation
- Feature extraction by non-linear methods
- ISOMAP, Locally Linear Embedding (LLE), Self Organizing Maps (SOM)
- Visualization for data pre-processing.
