decision tree

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Decision tree

Schematic way of representing alternative sequential decisions and the possible outcomes from these decisions.

Decision Tree

In risk analysis, a diagram of decisions and their potential consequences. It is used to help determine the most straightforward (and cheapest) way to arrive at a stated goal. It is represented by potential decisions (drawn as squares), branching off into different proximate consequences (drawn as circles), and potential end results (drawn as triangles).
Fig.32 Decision tree. The businessman has two options: to open a new factory to boost production capacity or not to open a new factory; and he has to consider two states of nature or events which can occur economic boom or recession. The businessman must assess the likelihood of each of these events occurring and, in this case, based on his knowledge and experience, he estimates that there is a one-in-two chance of a boom and a 0.5 probability of a recession. Finally, the businessman estimates the financial consequences as an £80,000 profit for the new factory if there is a boom, and a £30,000 loss if there is a recession.click for a larger image
Fig.32 Decision tree. The businessman has two options: to open a new factory to boost production capacity or not to open a new factory; and he has to consider two states of nature or events which can occur economic boom or recession. The businessman must assess the likelihood of each of these events occurring and, in this case, based on his knowledge and experience, he estimates that there is a one-in-two chance of a boom and a 0.5 probability of a recession. Finally, the businessman estimates the financial consequences as an £80,000 profit for the new factory if there is a boom, and a £30,000 loss if there is a recession.

decision tree

an aid to decision-making in uncertain conditions, that sets out alternative courses of action and the financial consequences of each alternative, and assigns subjective probabilities to the likelihood of future events occurring. For, example, a firm thinking of opening a new factory the success of which will depend upon consumer spending (and thus the state of the economy) would have a decision tree like Fig. 32.

In order to make a decision, the manager needs a decision criterion to enable him to choose which he regards as the best of the alternatives and, since these choices involve an element of risk, we therefore need to know something about his attitudes to risk. If the manager were neutral in his attitude to risk then we could calculate the certainty equivalent of the ‘open factory’ alternative using the expected money value criterion, which takes the financial consequence of each outcome and weights it by the probability of its occurrence, thus:

which being greater than the £0 for certain of not opening the factory would justify going ahead with the factory project.

However, if the manager were averse to risk then he might not regard the expected money value criterion as being appropriate, for he might require a risk premium to induce him to take the risk. Application of a more cautious certainty equivalent criterion would reduce the certainty equivalent of the ‘open factory’ branch and might even tip the decision against going ahead on the grounds of the ‘downside risk’ of losing £30,000.See UNCERTAINTY AND RISK.

decision tree

a graphical representation of the decision-making process in relation to a particular economic decision. The decision tree illustrates the possibilities open to the decision-maker in choosing between alternative strategies. It is possible to specify the financial consequence of each ‘branch’ of the decision tree and to gauge the PROBABILITY of particular events occurring that might affect the consequences of the decisions made. See RISK AND UNCERTAINTY.
References in periodicals archive ?
Decision Tree (DT) approach is used to analyze the data in the form of tree.
step4 : Construct decision tree and use it to predict efficiency score of other DMUs with the same attribute.
Traditionally decision trees are tree-like in appearance with each branch node representing a particular choice between a number of alternatives and each leaf node representing a classification or decision.
To resolve unclassifiable region in conventional OvO, decision tree OvO SVM formulation is proposed [19].
To help the user to choose the right routine decision trees are invaluable.
Decision trees can also perform efficiently in classification tasks.
The strategy of dividing the character recognition problem comprising several hundred classes into two 'orthographically orthogonal' decision trees is perhaps unique.
Thus if one class is much larger than another, as is the case with Fickett and TungOs benchmark training sets, decision trees tend to optimize accuracy on the larger class.
Key words: regression analysis, banks' profitability, forecasting, regression analysis, decision trees
From decision trees, graduate student Tao Shi of the Department of Human Genetics at the University of California, Los Angeles, took the audience into the woods as he described the use of "random forest" predictors to derive information from microarray data.
Stakeholder pensions, which have charges capped at one per cent, are designed to be sold without the need for advice, and are accompanied by decision trees to help consumers assess whether they are suitable for them.
It is important to note that decision trees, like data mining techniques, serve only to report to the user, who then makes a final decision regarding action and follow-up.