Difference between revisions of "Decision tree"
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A decision tree is a tree representing the logical structure of certain algorithms on various inputs. The nodes of the tree represent branch points of the computation — places where more than one outcome are possible based on some predicate of the input — and the leaves represent possible outcomes. Given a particular input, one starts at the root of the tree, performs the test at that node, and descends accordingly into one of the subtrees of the root. Continuing in this way, one reaches a leaf node which represents the outcome of the computation. | A decision tree is a tree representing the logical structure of certain algorithms on various inputs. The nodes of the tree represent branch points of the computation — places where more than one outcome are possible based on some predicate of the input — and the leaves represent possible outcomes. Given a particular input, one starts at the root of the tree, performs the test at that node, and descends accordingly into one of the subtrees of the root. Continuing in this way, one reaches a leaf node which represents the outcome of the computation. | ||
| + | <ref>László Lovász and Neal E Young. “Lecture notes on evasiveness of graph properties”. In: arXiv preprint cs/0205031 (2002).</ref> | ||
Revision as of 11:22, 27 February 2022
A decision tree is a tree representing the logical structure of certain algorithms on various inputs. The nodes of the tree represent branch points of the computation — places where more than one outcome are possible based on some predicate of the input — and the leaves represent possible outcomes. Given a particular input, one starts at the root of the tree, performs the test at that node, and descends accordingly into one of the subtrees of the root. Continuing in this way, one reaches a leaf node which represents the outcome of the computation.
- ↑ László Lovász and Neal E Young. “Lecture notes on evasiveness of graph properties”. In: arXiv preprint cs/0205031 (2002).
