Decision Tree and Its Application Term Paper:
A decision tree is applied in the sphere of statistics and data analysis for the predicted models.
The structure of the tree contains such elements: leaves and branches. The branches always contain the attributes which influence the target function; the values of the target function are written on the leaves. There are other nodes where one can find the attributes which differ according to the cases of their application. In order to classify the new case one should come down the tree to the leaves and give a certain value. The decision trees of this type are often used in the intellectual data analysis. The aim of the decision tree is the creation of the model which predicts the value of the target variable on the basis of a few input variables. Every leave written on the papers means the value of the target variable in the direction from the root of the tree. Every inner node meets one of the input variables.
Decision trees are quite useful on practice, because they enable people to understand the strong and the weak sides of the certain chosen decision or strategy and provides when with the solution of the problem with the help of the presentation of the different scenarios. Then, a decision tree can easily cooperate with other techniques used for the process of decision making and as a result one receives a more constructive and quality decision.
Although, decision trees are extremely useful on practice, there can be problems with this technique if the issue under research is too broad and complicated and requires heavy calculation, which can only confuse the expert.
Decision tree and its application can be called a useful and informative topic for every student who is interested in statistics and looks for the new effective techniques and methods of decision making. The young professional is supposed to dwell on the explanation of decision tree and the analysis of its structure, main elements, strong and weak sides. It is a plus to analyze the application of decision trees on practice and mention the types of the situations where the technique can be useful. The student is expected to observe the problem from all sides and draw the wise conclusion about the usefulness of the technique of decision trees.
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