Indução de Árvores de Decisão

Algoritmo TDIDT
[C4.5, Quinlan, 1993]
Generate_tree(R, C, T)
// R: set of non-categorical attribute
// C: categorical attribute, T: training data
1. if T has the same categorical value then return a single node with
the value
2. if R={} then return a single node with most frequent categorical
value in T
3. A = attribute with highest information gain, Gain(T,A) among R
4. Let A 1 , A 2 , .., A m the attribute values of A
5. Let T 1 , T 2 , .., T m the subsets of T partitioned by of A i
6. return a node with A and m links as follows
7. for i = 1 to m do
1. Generate_tree(R-{A}, C, T i )
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