Decision tree analysis is a method of evaluating the way in which users perform their own tasks. This is normally done through observations and interviews. In fact, a decision tree is created to model options in which a user must choose in order to perform tasks. A decision tree can also be defined as a graphical representation of an illustration, algorithm, costs, consequences, and utility. The following are the major benefits of the decision tree analysis:
1. Ease of use
The Decision Tree is very easy to use. This is because it provides a graphical representation of the problem and different types of alternatives in an easy and simple format which require no illustration. Normally, it is based on rules which can be used easily be human as well as the SQL programs. It can also allow classification of data without the need of computation.
2. It is flexible
Other decision making tools requires quantitative and comprehensive tools. However, the decision trees are flexible as it will handle items with a mixture of categories and features of real value. When they have been constructed, they classify new items very fast.
With the decision tree, it can enable validation since it is the best predictive model. In fact, it finds use of making quantitative analysis of the business platform. In addition, it can validate results of the statistical tests. Nevertheless, it can support naturally the classification of problems with several classes by modification process.
Another advantage of the decision tool is that it focuses on the relationships of different types of events. In addition, it replicates the natural course of events. The ability of the decision tree allows incorporation in various applications. It has also enabled the combination of other decision making techniques for example linear distributions and Perth charts.
5. The comprehensive nature
Decision Tree is one of the best predictive models. This is because it enables compressive analysis of consequences of very possible decision. The comprehensive nature also allows the partitioning of data in a very deep level as compared to the other decision making tools.
This is one of the major decision tree analysis as it has the ability to assign specific values to outcomes, decisions and problems. Consequently, it will reduce the ambiguity in the decision making process. Nevertheless, it enables viewing of all the possible solutions in a single view.
Transparency is also one of the advantages of the Decision Tree Analysis. The decision making model explicit all possible alternatives to conclusion within a single view. They use separate nodes for denoting user defined decisions, end process and uncertainties. As a result, it will lead to further transparency and clarity to the decision making process.
In conclusion, Decision Tree is beneficial . The decision tree is of great significance since it will provide you with benefits such as clarity, specify and other advantages mentioned. As opposed to a typical user, the decision tree may be developed by a domain expert. This has assisted in optimizing the decision making performance. Nevertheless, the decision tree is used as a resource for designing the user tasks. Therefore, you need to use the decision tree because of the benefits highlighted.