3-3 minutes<\/p>\n
A decision tree is a pictorial description of a well-defined decision problem. A decision tree describes graphically the decisions to be made, the events that may occur, and the outcomes associated with combinations of decisions and events.<\/p>\n
If probabilities are assigned to the events, and values are determined for each outcome by calculating the expected value of each available alternative. Decision trees are useful because they provide a clear, documentable and discussible model of either how the decision was made or how it will be made. A major goal of the analysis is to determine the best decisions.<\/p>\n
Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning.<\/p>\n
We can start from the root node which contains an attribute of Travel cost per km.<\/p>\n
1. If the travel cost per km is expensive, the person uses a car.<\/p>\n
2. If the travel cost per km is the standard price, the person uses a train.<\/p>\n
3. If the travel cost is cheap, the decision tree needs to ask the next question about the gender of the person. If the person is a male, then he uses a bus.<\/p>\n
4. If the gender is female, the decision tree needs to ask again how many cars she owns in her household.<\/p>\n
5. If she has no car, she uses a bus,<\/p>\n
6. Otherwise, she uses the train.<\/p>\n
Edit this Diagram<\/p>\n
This is a decision tree example created with the Decision Tree tool. It shows what and how a purchase decision is made. Let\u2019s take a path as an example \u2013 If the color of the vehicle is red and was launched after 2010, buy it.<\/p>\n","protected":false},"excerpt":{"rendered":"