From Predictive Algorithms to Automatic Generation of Anomalies
Machine learning algorithms can find predictive signals that researchers fail to notice; yet they are notoriously hard-to-interpret. How can we extract theoretical insights from these black boxes? History provides a clue. Facing a similar problem – how to extract theoretical insights from their intu...
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| Published in: | NBER Working Paper Series |
|---|---|
| Main Authors: | , |
| Format: | Paper |
| Language: | English |
| Published: |
Cambridge
National Bureau of Economic Research, Inc
01.05.2024
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| Subjects: | |
| ISSN: | 0898-2937 |
| Online Access: | Get full text |
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