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by Graham Williams
Duck Duck Go


Rattle View Decision Tree

Image rattle_weather_rpart_fancy

Click the Draw button to display the decision tree. A visual representation is often simpler to understand.

For a classification tree as we have here colour is used to differentiate the predicted (majority) class for each node. For our example the class/decision No is green and Yes is blue. The intensity of the colour indicates the strength of the prediction which is proportional to the percentage of the majority class within that node.

The root node (node number 1) has 84% No and 16% Yes and so is reported as a No decision or class. That is, in the absence of any other information, we predict that it will not rain tomorrow, and expect that prediction to be 84% correct.

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Other online resources include the GNU/Linux Desktop Survival Guide.
Books available on Amazon include Data Mining with Rattle and Essentials of Data Science.
Popular open source software includes rattle and wajig.
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