• 1. Wavelength Point Selection
  • 1.1. Variable Importance in Projection
  • 1.2. Monte-Carlo Uninformative Variable Elimination
  • 1.3. Random Frog
  • 1.4. Competitive Adaptive Reweighted Sampling
  • 1.5. Successive Projection Algorithm
  • 1.6. Variable Iterative Subspace Shrinkage Approach
• 2. Wavelength Interval Selection
  • 2.1. Interval Partial Least Squares
  • 2.2. Forward Interval Partial Least Squares
  • 2.3. Backward Interval Partial Least Squares
  • 2.4. Interval Random Frog
• 3. Adding Selectors to Auswahl
  • 3.1. PointSelector to IntervalSelector conversion
  • 3.2. Preparing the selector for benchmarking
• 4. Benchmarking
  • 4.1. Data sets
  • 4.2. Selectors
  • 4.3. Features to select
  • 4.4. Metrics
  • 4.5. Benchmarking Results
  • 4.6. Plotting Facilities
  • 4.7. Error logging
  • 4.8. Miscellaneous