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Implement Feature Engineering for GDP Prediction Model #608
Description:
In the "GDP Prediction" section (gdp-prediction-model.ipynb) I aim to enhance the predictive power of our models by implementing feature engineering techniques. This involves creating new features derived from existing ones to capture additional information relevant to GDP prediction.
Proposed Feature Engineering Ideas:
GDP Growth Rate: Calculate the percentage change in GDP over time to capture economic growth trends.
Population Density: Compute the population density by dividing the population by the land area.
Urbanization Rate: Determine the proportion of the population living in urban areas, reflecting economic development.
Objective:
Enhance model accuracy and robustness by implementing feature engineering techniques in the GDP prediction model.
Tasks:
Research and identify relevant economic indicators for feature engineering.
Implement feature engineering techniques, including GDP growth rate, population density, and urbanization rate calculations.
Evaluate the impact of new features on model performance using appropriate evaluation metrics.
Description: In the "GDP Prediction" section (
gdp-prediction-model.ipynb
) I aim to enhance the predictive power of our models by implementing feature engineering techniques. This involves creating new features derived from existing ones to capture additional information relevant to GDP prediction.Proposed Feature Engineering Ideas:
Objective: Enhance model accuracy and robustness by implementing feature engineering techniques in the GDP prediction model.
Tasks: