Decision Trees
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Decision Trees

DECISION TREE

An internal node is a test on an attribute.
A branch represents an outcome of the test, e.g., Color=red.
A leaf node represents a class label or class label distribution.
At each node, one attribute is chosen to split training examples into distinct classes as much as possible
A new case is classified by following a matching path to a leaf node.

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Messages In This Thread
Decision Trees - by project report helper - 26-10-2010, 11:47 AM
RE: Decision Trees - by project report helper - 26-10-2010, 01:24 PM

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