Surrogate Data Models: Interpreting Large-scale Machine Learning Crisis Prediction Models

Download or read book Surrogate Data Models: Interpreting Large-scale Machine Learning Crisis Prediction Models written by Mr. Jorge A Chan-Lau and published by International Monetary Fund. This book was released on 2023-02-24 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs model interpretability and their ability to provide adequate guidance in the design of crisis prevention and mitigation policies. This paper introduces surrogate data models as dimensionality reduction tools in large-scale crisis prediction models. The appropriateness of this approach is assessed by their application to large-scale crisis prediction models developed at the IMF. The results are consistent with economic intuition and validate the use of surrogates as interpretability tools.