Name
Title | ||
|---|---|---|
Online sequential prediction of imbalance data with two-stage hybrid strategy by extreme learning machine. |
Abstract | ||
|---|---|---|
•We derive an efficient leave-one-out cross-validation error estimate for OS-ELM.•We propose a two-stage hybrid strategy for online sequential data imbalance problem.•We prove theoretically the rationality and validity of this strategy.•We proposed a new OS-ELM method for solving online sequential data imbalance problem.•We conduct a number of computer experiments on UCI and real-life data sets. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.neucom.2016.05.111 | Neurocomputing |
Keywords | Field | DocType |
Extreme learning machine,Imbalance problem,Principal curve,Leave-one-out cross-validation,Online sequential learning | Data mining,Online machine learning,Active learning (machine learning),Extreme learning machine,Computer science,Support vector machine,Woodbury matrix identity,Artificial intelligence,Classifier (linguistics),Cross-validation,Machine learning,Numerical stability | Journal |
Volume | ISSN | Citations |
261 | 0925-2312 | 3 |
PageRank | References | Authors |
0.37 | 19 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wentao Mao | 1 | 112 | 11.54 |
| Jinwan Wang | 2 | 37 | 1.83 |
| Ling He | 3 | 52 | 6.94 |
| Yangyang Tian | 4 | 4 | 0.73 |