Improving the Performance of the RISE Algorithm

Ideally, a multi-strategy learning algorithm performs better than its component approaches. RISE is a multi-strategy algorithm that combines rule induction and instance-based learning. It achieves higher accuracy than some state-of-the-art learning algorithms, but for large data sets it has a very high average running time. This work presents the analysis and experimental evaluation of SUNRISE, a new multi-strategy learning algorithm based on RISE. The SUNRISE algorithm was developed to be faster than RISE with similar accuracy. Comparing the results of the experimental evaluation of the two algorithms, it could be verified that the new algorithm achieves comparable accuracy to that of the RISE algorithm but in a lower average running time.

• Type: Conference
• Year: 2004
• Where: PKDD
• Authors: Aloísio Carlos de Pina, Gerson Zaverucha
• Keywords: Average Running Time, Multi-strategy Algorithm, Multi-strategy Learning Algorithm, PKDD 2004