Dimensionality Reduction

Dimensionality Reduction

RM 2,000.00

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.