A decision trees represents complex rules as a series of simple conditions with sub-trees (branches) for further conditons depending in the outcome to the inital condition. Decsion trees can be hand crafted (e.g. decison trees in IVR), but most commonly encountered in AI as the output of machine learning algorithms such as Quinlan's ID3 or C4.5, or as part of a random forest.
Used on Chap. 5: pages 98, 106; Chap. 6: pages 124, 125; Chap. 8: page 163; Chap. 9: pages 176, 183, 188; Chap. 10: page 204; Chap. 16: pages 386, 387; Chap. 18: page 439; Chap. 19: page 463; Chap. 21: pages 517, 519, 520, 522, 523, 526, 528; Chap. 24: page 584
Also known as decision trees
A simple decision tree