UnFEAR : Unsupervised Feature Extraction Clustering with an Application to Crisis Regimes Classification.
We introduce unFEAR, Unsupervised Feature Extraction Clustering, to identify economic crisis regimes. Given labeled crisis and non-crisis episodes and the corresponding features values, unFEAR uses unsupervised representation learning and a novel mode contrastive autoencoder to group episodes into t...
| التنسيق: | دورية |
|---|---|
| اللغة: | English |
| منشور في: |
Washington, D.C. :
International Monetary Fund,
2020.
|
| سلاسل: | IMF Working Papers; Working Paper ;
No. 2020/262 |
| الوصول للمادة أونلاين: | Full text available on IMF |