Decision tree can be defined as a tool to support decision made. This is usually in the form of tree like graph or model that
includes everything that can be used for supporting the decisions. In other words, it can be said that the decision tree helps in analyzing the decision where the expected values or expected utility of alternatives, that are competitive in nature, are calculated.
There are 3 types of nodes that are used in decision tree:
Decision nodes -represented by squares
Chance nodes - represented by circles
End nodes - represented by triangles.
This tree is drawn form left to right and this has only splitting paths other than the 3 nodes mentioned above. Due to its simplicity, this tool is easy to interpret and understood by people.
The decision tree models are mostly used in operations research(for decision analysis) and which helps to identify the strategy used to achieve a goal. Other than operations research, this tool is also used in statistics, data mining and machine learning(helps in describing a data and not decisions).
Procedure for decision tree is as follows:
Start with a decision that need to be made which is drawn in a square and starts form left
From this square, a line is drawn towards right, which represents the solution and needs to be written on top of the line. for example, if a particular problem has 2 solutions, draw 2 lines representing these solutions.
For each of the solution, the result will be written at the end of the line
If the result in uncertain or a chance is to be taken, a circle is drawn and from it a line is drawn outwards with that information and if the result involves taking another decision, a square is drawn with that decision written on the lines drawn from that square.
In this way, decision tree is drawn till a solution is made to that problem. when the solution is made, nothing needs to be done at the end of the line.
