Name
Abstract | ||
|---|---|---|
In this paper, an approach to autonomous learning of a multimodel system from streaming data, named ALMMo, is proposed. The proposed approach is generic and can easily be applied also to probabilistic or other types of local models forming multimodel systems. It is fully data driven and its structure is decided by the nonparametric data clouds extracted from the empirically observed data without m... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TFUZZ.2017.2769039 | IEEE Transactions on Fuzzy Systems |
Keywords | Field | DocType |
Clouds,Data analysis,Learning systems,Data models,Meteorology,Computational modeling,Wavelet transforms | Data modeling,Data mining,Data stream mining,Data-driven,Computer science,Nonparametric statistics,Artificial intelligence,Probabilistic logic,Analytics,Machine learning,Recursion,Cloud computing | Journal |
Volume | Issue | ISSN |
26 | 4 | 1063-6706 |
Citations | PageRank | References |
10 | 0.64 | 23 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Plamen Angelov | 1 | 954 | 67.44 |
| Xiaowei Gu | 2 | 99 | 10.96 |
| José C. Principe | 3 | 46 | 5.08 |