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 pages 99, 107, 124, 125, 163, 176, 183, 187, 188, 204, 386, 387, 439, 463, 517, 519, 520, 522, 523, 526, 528, 584
Also known as decision trees
A simple decision tree