Description:... 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.
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* نتیجه بررسی از طریق ایمیل ارسال خواهد شد
شماره کارت : 6104337650971516 شماره حساب : 8228146163 شناسه شبا (انتقال پایا) : IR410120020000008228146163 بانک ملت به نام مهدی تاج دینی