Name
Abstract | ||
|---|---|---|
One of the most informative measures for feature extraction (FE) is mutual information (MI). In terms of MI, the optimal FE creates new features that jointly have the largest dependency on the target class. However, obtaining an accurate estimate of a high-dimensional MI as well as optimizing with respect to it is not always easy, especially when only small training sets are available. In this pap... |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TNNLS.2011.2178447 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | DocType | Volume |
Feature extraction,Iron,Estimation,Mutual information,Entropy,Approximation methods,Frequency modulation | Journal | 23 |
Issue | ISSN | Citations |
1 | 2162-237X | 14 |
PageRank | References | Authors |
0.70 | 19 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farid Oveisi | 1 | 23 | 1.72 |
| Shahrzad Oveisi | 2 | 14 | 1.04 |
| Abbas Erfanian | 3 | 58 | 7.35 |
| Ioannis Patras | 4 | 1960 | 123.15 |