MAT week2

MAT week2 - by non-technical people. For example, if the...

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Decision Trees are excellent tools for helping you to choose between several courses of action. They provide a highly effective structure within which you can lay out options and investigate the possible outcomes of choosing those options. And also a decision support tool that uses a tree –like graph or model of decisions and their possible consequences. They also help you to form a balanced picture of the risks and rewards associated with each possible course of action. The primary advantage of a decision tree is that it assigns exact values to the outcomes of different actions, thus minimizing the ambiguity of complicated decisions. http://www.referenceforbusiness.com/encyclopedia/Cos-Des/Decision-Tree.html Using a Decision Tree Once DTREG has created a decision tree, you can use it in the following ways: You can use the tree to make inferences that help you understand the “big picture” of the model. One of the great advantages of decision trees is that they are easy to interpret even
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Unformatted text preview: by non-technical people. For example, if the decision tree models product sales, a quick glance might tell you that men in the South buy more of your product than women in the North. If you are developing a model of health risks for insurance policies, a quick glance might tell you that smoking and age are important predictors of health. • You can use the decision tree to identify target groups. For example, if you are looking for the best potential customers for a product, you can identify the terminal nodes in the tree that have the highest percentage of sales, and then focus your sales effort on individuals described by those nodes. • You can predict the target value for specific cases where you know only the predictor variable values. This is known as “ scoring ”. http://www.dtreg.com/dtintro.htm...
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This note was uploaded on 02/10/2012 for the course MAT 540 taught by Professor Dralexander during the Spring '11 term at Strayer.

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