Name
Abstract | ||
|---|---|---|
This work reports the research on active learning approach applied to the data stream classification. The chosen characteristics of the proposed frameworks were evaluated on the basis of the wide range of computer experiments carried out on the three benchmark data streams. Obtained results confirmed the usability of proposed method to the data stream classification with the presence of incremental concept drift. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-32034-2_16 | Hybrid Artificial Intelligent Systems |
Keywords | Field | DocType |
Pattern classification, Data stream classification, Active learning | Computer experiment,Data stream mining,Active learning,Pattern recognition,Computer science,Data stream,Usability,Concept drift,Streaming data,Artificial intelligence,Classifier (linguistics),Machine learning | Conference |
Volume | ISSN | Citations |
9648 | 0302-9743 | 2 |
PageRank | References | Authors |
0.39 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michal Wozniak | 1 | 764 | 83.90 |
| Boguslaw Cyganek | 2 | 145 | 24.53 |
| Andrzej Kasprzak | 3 | 88 | 20.35 |
| Pawel Ksieniewicz | 4 | 17 | 6.38 |
| Krzysztof Walkowiak | 5 | 450 | 59.98 |