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Creating a Dataset:

There are two ways to acquire a dataset to build a decision tree for:

• You can create a new dataset and input data examples. If you wish to create a new dataset, see the detailed help section on this topic (Tutorial 1).
• You can load a sample dataset.

To load a sample dataset:

1. Click "Load Sample Dataset" from the "File" menu.
2. Select a dataset from the drop-down menu and click "Load."
3. Click the "View/Edit Examples" button near the top of the left-side control panel to view and manipulate the examples in the data set. This opens a dialog window that can be used to add examples, remove examples, and transfer examples between the training set (left side) and the test set (right side). Make sure there are several examples in the test set before proceeding to build the decision tree.

Creating and Testing a Decision Tree:

Now that you have a dataset ready, select the "Solve" tab at the top of the message panel (below the toolbar). There are two ways to build a decision tree:

• This can be done automatically by clicking the "Step" button until the tree is complete.
• Alternatively, you can use the "Split Node" option from the tool bar menu to construct the tree yourself.

The other node options: "View Node Information," "View Mapped Examples," and "Toggle Histogram" can be used to gain information about the data at a particular node to guide your splitting.

Before or anytime during the construction a decision tree, you may wish to click the "Show Plot" button to view the changes in training set and test set error as the tree is built.

Once the decision tree is built, you can now test your decision tree to see how well it could classify the test examples. This will open a window that shows which examples were correctly predicted, which were incorrectly predicted, and those for which the tree cannot make a prediction. The pie chart at the bottom provides a quick indication of the decision tree's performance.