In order to explain decision trees, it's important to remember that they are rational models and also visual decision tools.
They are rational because they're used to compare consequences and potential value of each of the decision making options in order to come up with the best possible alternative.
They are visual tools in that they allow you to organise a lot of complex information graphically.
Decision trees obviously include the options that are available. And for each option it may include many consequences, further decisions that may arise, the probability of its occurrence, the cost of, and the potential value as a result of choosing this option.
Decision trees are commonly used in computing in order to calculate probabilities and for data mining, so it figures that there are many computers that will create them.
In order to further explain these trees, it makes sense to have a look at some examples...
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