Enhanced Feature Engineering for Crisis Prediction #296
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Hi @Akshat111111 , Please assign labels GSSOC and level 2 to this PR. Resolves #266 . |
Akshat111111
reviewed
Jun 5, 2024
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Hi @Akshat111111 , I have changed the file name to "African_Crisis_Prediction.ipynb". Please check now. |
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🎉 Your pull request has been successfully merged! 🎉 Thank you for your contribution to our project. Your efforts are greatly appreciated. Keep up the fantastic work! 🚀 |
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Enhancing Feature Engineering for Banking Crisis Prediction Model
Description:
The code introduces several feature engineering techniques to improve the predictive performance of the banking crisis prediction model.
Interaction Terms: Multiplication of 'systemic_crisis' and 'domestic_debt_in_default' to capture their interaction effect.
Ratio Features: Calculation of the ratio between 'exch_usd' and 'inflation_annual_cpi' to provide a normalized exchange rate.
Moving Averages: Computation of the 3-month moving average of 'gdp_weighted_default' to smooth out short-term fluctuations.
Difference Features: Calculation of the difference in 'inflation_annual_cpi' between consecutive years to capture changes over time.
Categorical Aggregations: Aggregation of mean inflation rates for each level of the 'banking_crisis' variable to provide additional insights.
These feature engineering techniques aim to extract more meaningful information from the existing data, potentially enhancing the model's ability to predict banking crises in African economies.