Abstract
In this paper we introduce a variation of the performance phase of Fuzzy ARTMAP which is called Fuzzy ARTVar. Experimental results have shown that Fuzzy ARTVar exhibits superior generalization performance, compared to Fuzzy ARTMAP, for a variety of machine learning databases. Furthermore, experimental results have also demonstrated that Fuzzy ARTVar compares favorably with other existing variations of Fuzzy ARTMAP, such as ARTEMAP (power rule), ARTEMAPQ (Q-max rule), and Gaussian ARTMAP. What is worth noting is that the performance of Fuzzy ARTVar is independent of the tuning of network parameters, in contrast with the ARTEMAP, ARTEMAPQ, and Gaussian ARTMAP algorithms, whose performances depends on the choice of certain network parameters.
| Original language | English (US) |
|---|---|
| Pages | 1688-1693 |
| Number of pages | 6 |
| State | Published - 1998 |
| Externally published | Yes |
| Event | Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) - Anchorage, AK, USA Duration: May 4 1998 → May 9 1998 |
Conference
| Conference | Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) |
|---|---|
| City | Anchorage, AK, USA |
| Period | 5/4/98 → 5/9/98 |
ASJC Scopus subject areas
- Software