Title :
The RISE system: conquering without separating
Author_Institution :
Dept. of Inf. & Comput. Sci., California Univ., Irvine, CA, USA
Abstract :
Current rule induction systems (e.g. CN2) typically rely on a “separate and conquer” strategy, learning each rule only from still-uncovered examples. This results in a dwindling number of examples being available for learning successive rules, adversely affecting the system´s accuracy. An alternative is to learn all rules simultaneously, using the entire training set for each. This approach is implemented in the RISE 1.0 system. Empirical comparison of RISE with CN2 suggests that “conquering without separating” performs similarly to its counterpart in simple domains, but achieves increasingly substantial gains in accuracy as the domain difficulty grows
Keywords :
knowledge based systems; learning by example; CN2; RISE system; conquering; divide and conquer; domain difficulty; rule induction systems; separate and conquer; still-uncovered examples; successive rules; training set; Computer science; Machine learning; Machine learning algorithms; Performance gain;
Conference_Titel :
Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-8186-6785-0
DOI :
10.1109/TAI.1994.346421