Desktop Survival Guide
by Graham Williams


Complexity: Generally C4.5 is quite efficient as the number of training instances increases, and for specific datasets has been found empirically to be between $O(n^{1.22})$ and $O(n^{1.38})$. With rule generation the algorithm is somewhat more expensive at $O(n^4)$.
Availability: The Borgelt collection (See Chapter [*]) contains dtree, a generic implementation of the decision tree divide and conqueror algorithm. Weka (See Chapter [*]) also provides a freely available implementation of a decision tree induction algorithm (J48) within its Java-based framework. Decision tree induction is a fundamental data mining tool and implementations of C4.5 or its variations are available in most commercial data mining toolkits, including Clementine (See Chapter [*]) and STATISTICA (See Chapter [*]).

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