Name
Abstract | ||
|---|---|---|
This paper analyzes a generalization of a new metric to evaluate the classification performance in imbalanced domains, combining some estimate of the overall accuracy with a plain index about how dominant the class with the highest individual accuracy is. A theoretical analysis shows the merits of this metric when compared to other well-known measures. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPR.2010.156 | ICPR |
Keywords | Field | DocType |
theoretical analysis,imbalanced domain,overall accuracy,plain index,well-known measure,performance measure,imbalanced data,classification performance,highest individual accuracy,indexation,indexes,learning artificial intelligence,correlation,measurement uncertainty,accuracy | Data mining,Pattern recognition,Computer science,Measurement uncertainty,Correlation,Artificial intelligence,Machine learning | Conference |
Citations | PageRank | References |
12 | 0.66 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vicente García | 1 | 78 | 6.37 |
| Ramón A. Mollineda | 2 | 383 | 20.41 |
| José Salvador Sánchez | 3 | 184 | 15.36 |