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Description:
Learning is the ability to improve one's behaviour based on
experience and represents an essential element of computational
intelligence. Decision trees are a simple yet successful
technique for supervised classification learning. This tool
demonstrates how to build a decision tree using a training data
set and then use the tree to classify unseen examples in a test
data set.
Please visit our
feedback page and send us your comments about the tools!
This tool was written by Kevin O'Neill, Shinjiro Sueda, Wesley Coelho, Oxana Chakoula, Nicole Arksey, Kyle Porter, and Byron Knoll, with help from David Poole, Alan Mackworth, Holger Hoos, Peter Gorniak, Giuseppe Carenini, and Cristina Conati.
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Video Tutorial