Name
Abstract | ||
|---|---|---|
•Assume each classifier has different predictive ability on different instances.•Embed classifiers and instances into the same latent space.•Design an explicit diversity measure of classifiers in the latent space.•Learn personalized weights of classifiers w.r.t instances for classifier ensemble. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.patcog.2019.106976 | Pattern Recognition |
Keywords | Field | DocType |
Multiple classifier system,Ensemble learning,Attentional mechanism,Diversity-based learning | Data set,Ensemble forecasting,Diversity measure,Pattern recognition,Artificial intelligence,Invariant (mathematics),Classifier (linguistics),Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
96 | 1 | 0031-3203 |
Citations | PageRank | References |
2 | 0.39 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongzhi Liu | 1 | 88 | 14.92 |
| Yingpeng Du | 2 | 4 | 2.78 |
| Zhonghai Wu | 3 | 34 | 12.36 |