|Title||One-class classifiers based on entropic spanning graphs|
|Publication Type||Journal Article|
|Year of Publication||2017|
|Authors||Livi, L., and C. Alippi|
|Journal||IEEE Transactions on Neural Networks and Learning Systems|
|Pagination||2846 - 2858|
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. The spanning graph is learned on the embedded input data, with the aim to generate a partition of the vertices.