Parallelepiped (2) — when to use it.

• Limits can be anything the user specifies — e.g., min/max of training data, or ±1 or ±2 σ.
• Advantages:
  • Very simple, very fast.
  • Good as a first-pass broad classification.
• Disadvantages:
  • Gap regions (pixels outside all boxes) stay unclassified.
  • Corners where boxes overlap may be assigned incorrectly.