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Decision Trees

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Decision trees

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Decision trees
A decision tree is a visual tool for analysing decisions. In using it, you generate a tree-like graph of decisions and their consequences. In the simplest form of this technique Squares represent decisions Triangles represent end points. Jewish proverb When the graph is completed, you can then add probabilities for each of the individual branches and from the overall probabilities of the end points. If there are two courses of action, you should take the third.

Using the technique
As a simple example, let’s suppose that I decide that I want to travel from my home to a hotel in town A. So let’s draw the options in a decision tree: We can now add some percentages to reflect either our preferences or an estimate of some factor that we would like to consider (for example cost, estimated likelihood and so on). In this case, I will use personal preferences:

I am assuming here that the train station is close to my home. For ‘walk’ I have added 0 per cent because it is a long distance to town A. The bus takes a long time, but it is quite cheap, so I have given it ten per cent. Notice that I have also added end points to ‘walk’ and ‘drive’ as they both get me to my destination. ‘Train’ and ‘bus’ however do not get me to my final destination, so I now extend my decision tree by adding more decision points, options and estimates:

We can now see what the final end point percentages are. To do this, we work out, for example, that 50 per cent (the train) of 90 per cent (taxi) is 45 per cent and so on:

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16/06/2014 23:03

Decision trees

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So our conclusion should be that we should take the train and a taxi (45 per cent).

Extending the percentages
In this example, I have used personal…...

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