Name
Title | ||
|---|---|---|
Reduction strategies for hierarchical multi-label classification in protein function prediction. |
Abstract | ||
|---|---|---|
The experiments showed that using the output in one level as input to the next level contributed to better classification results. We believe the method was able to learn the relationships between the protein functions during training, and this information was useful for classification. We also identified in which functional classes our method performed better. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12859-016-1232-1 | BMC Bioinformatics |
Keywords | Field | DocType |
Hierarchical multi-label classification,Machine learning,Neural networks,Protein function prediction | Feature vector,Computer science,Multi-label classification,Artificial intelligence,Bioinformatics,Artificial neural network,Hierarchy,Protein function prediction,Machine learning | Journal |
Volume | Issue | ISSN |
17 | 1 | 1471-2105 |
Citations | PageRank | References |
9 | 0.63 | 28 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ricardo Cerri | 1 | 132 | 16.88 |
| Rodrigo C. Barros | 2 | 448 | 32.54 |
| André C. P. L. F. de Carvalho | 3 | 517 | 41.24 |
| Yaochu Jin | 4 | 6457 | 330.45 |