Name
Abstract | ||
|---|---|---|
One-class classifiers offer valuable tools to assess the presence of outliers in data. In this paper, we propose a design methodology for one-class classifiers based on entropic spanning graphs. Our approach also takes into account the possibility to process nonnumeric data by means of an embedding procedure. The spanning graph is learned on the embedded input data, and the outcoming partition of ... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TNNLS.2016.2608983 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | DocType | Volume |
Entropy,Mutual information,Proteins,Feature extraction,Benchmark testing,Image coding,Random variables | Journal | 28 |
Issue | ISSN | Citations |
12 | 2162-237X | 1 |
PageRank | References | Authors |
0.35 | 38 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lorenzo Livi | 1 | 304 | 25.67 |
| Cesare Alippi | 2 | 1040 | 115.84 |