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This template is used on approximately 9,600 pages and changes may be widely noticed. Test changes in the template's /sandbox or /testcases subpages, or in your own user subpage . Consider discussing changes on the talk page before implementing them.
This template produces one row in a "family tree"-like chart consisting of boxes and connecting lines based loosely on an ASCII art-like syntax.It is meant to be used in conjunction with {{Tree chart/start}} and {{Tree chart/end}}.
Decision trees can also be seen as generative models of induction rules from empirical data. An optimal decision tree is then defined as a tree that accounts for most of the data, while minimizing the number of levels (or "questions"). [8] Several algorithms to generate such optimal trees have been devised, such as ID3/4/5, [9] CLS, ASSISTANT ...
Business decision mapping (BDM) is a technique for making decisions, particularly for the kind of decisions that often need to be made in business.It involves using diagrams to help articulate and work through the decision problem, from initial recognition of the need through to communication of the decision and the thinking behind it.
Decision tables are a concise visual representation for specifying which actions to perform depending on given conditions. Decision table is the term used for a Control table or State-transition table in the field of Business process modeling ; they are usually formatted as the transpose of the way they are formatted in Software engineering .
Value tree analysis is a multi-criteria decision-making (MCDM) implement by which the decision-making attributes for each choice to come out with a preference for the decision makes are weighted. [1] Usually, choices' attribute-specific values are aggregated into a complete method. Decision analysts (DAs) distinguished two types of utility. [2]
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An influence diagram (ID) (also called a relevance diagram, decision diagram or a decision network) is a compact graphical and mathematical representation of a decision situation. It is a generalization of a Bayesian network , in which not only probabilistic inference problems but also decision making problems (following the maximum expected ...