ID3

Name	ID3
Description	The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported. Depending on whether the attributes are nominal or numerical, the tests either have a successor for each possible attribute value, or split according to a comparison of an attribute value to a constant, or depending on if an attribute value belongs to a certain interval or not. The algorithm starts with the complete set of examples, a set of possible tests and the root node as the actual node. As long as the examples propagated to a node do not all belong to the same class and there are tests left, a test with highest information gain is chosen, the corresponding set of successors is created for the actual node, each example is propagated to the successor given by the chosen test, ID3 is called recursively for all successors.
Specialization	ID3 Software
Generalization	Top-Down Induction of Decision Trees (TDIDT)
Example Languages	Attribute-Value
Method Type	Algorithm
Measures	Information Gain