Name
Title | ||
|---|---|---|
Confusion-Matrix-Based Kernel Logistic Regression for Imbalanced Data Classification. |
Abstract | ||
|---|---|---|
There have been many attempts to classify imbalanced data, since this classification is critical in a wide variety of applications related to the detection of anomalies, failures, and risks. Many conventional methods, which can be categorized into sampling, cost-sensitive, or ensemble, include heuristic and task dependent processes. In order to achieve a better classification performance by formul... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TKDE.2017.2682249 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | Field | DocType |
Kernel,Linear programming,Logistics,Support vector machines,Training data,Harmonic analysis,Probabilistic logic | Kernel (linear algebra),Data mining,Heuristic,Confusion matrix,Computer science,Harmonic mean,Support vector machine,Heuristics,Artificial intelligence,Data classification,Probabilistic logic,Machine learning | Journal |
Volume | Issue | ISSN |
29 | 9 | 1041-4347 |
Citations | PageRank | References |
7 | 0.46 | 25 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miho Ohsaki | 1 | 195 | 28.23 |
| Peng Wang | 2 | 385 | 106.03 |
| kenji matsuda | 3 | 10 | 1.19 |
| Shigeru Katagiri | 4 | 850 | 114.01 |
| Hideyuki Watanabe | 5 | 37 | 8.46 |
| Anca L. Ralescu | 6 | 274 | 83.69 |