The purpose of this tutorial is to introduce how to create
basic decision trees in rapid minor. I will use a default dataset in rapid
minor, “Iris”, for the purposes of this tutorial.
1)
In order to access this data set, click the
processes tab to make sure you are in the correct window, then go to the
repository and click on the repository where it says data and open the drop
down menu to see the data set “Iris” as shown in the picture below.
2) Click and drag the data set into the main
processes window. Once the object representing the data set is in the window,
clock the bump on the back of it that says out. A line should appear. Connect
that line to the bump at the corner of the window, then hit run at the top of
the screen so that we can go look into the results tab to get a view of the
structure of this data set.
3)
Below, we can see the structure of the data we
intend to create the decision tree around. You will notice that there are four
attributes which are numerical data types and one attribute is a nominal label.
4)
Click the tab necessary to go back to the main
processes window. In the Operators menu
Click open the following drop down menus in this order: Modeling, Tree
induction, Decision Tree. Drag the decision tree icon into the main processes
window and make the connections shown in the picture below. After you have the
main processes window set up as picture below, click run and rapid miner will
take you to the output automatically.
5)
Below is the resulting output for this decision
tree from rapid minor using the default parameters for the rapid minor decision
tree. The trees root node (at the top of the tree) begins with the a3 node in order
to make decisions for classification. The results yield that for values in a3
which are less than or equal to 2.45, that can be shown to fully belong to the
group “iris-setosa”, as an example. As you go down the tree, you acquire more
and more criteria for some classification. For further instruction on the use of decision
trees in rapid minor, visit the rapid miner website.
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