Introduction
The Sustainable Development Goals (SDGs) are a set of 17 interlinked goals adopted by the United Nations in 2015 to address the world's most pressing challenges by 2030. These goals aim to ensure a more sustainable and equitable future for all, focusing on economic, social, and environmental dimensions. SDG 5 aims to achieve gender equality by ending all forms of discrimination, violence and any harmful practices against women and girls in the public and private spheres. It also calls for the full participation of women and equal opportunities for leadership at all levels of political and economic decision-making.
Selected SDG and Indicator
SDG Selected: SDG 5 - Gender Equality
Indicator Selected: Positions held by women in senior management positions with two sub indicators Board Members and Executives
Methodology
Data Processing
- Data Cleaning: Removing any missing or inconsistent values to ensure that the data is accurate and reliable for analysis.
- Feature Selection: By selecting the most relevant features or indicators from the data will help to improve the performance of machine learning models.
Machine Learning Models
Below we have the 3 models mentioned in this course
- Linear Regression;
- Random Forest Regression;
- Support Vector Regression (SVR);
Evaluation Metrics
- Mean Absolute Error (MAE);
- Mean Squared Error (MSE);
- R-Squared (R^2);
Results
Model 1 - Linear Regression
- Performance:
- MAE: 1.32
- MSE: 2.64
- R^2: 0.96
Model 2 - Random Forest Regression
- Performance:
- MAE: 1.3
- MSE: 2.6
- R^2: 0.95
Model 3 - SVR
- Performance:
- MAE: 1.28
- MSE: 2.58
- R^2: 0.98
Observations
I used the percentage of women as Board Members and used only the average value of UE between 2003 -2023. I'm not sure that the Random and SVR are well-calculated as it was not easy to find a proper implementation.
References
- PORDATA - Database for European statistics: PORDATA
- United Nations Sustainable Development Goals: SDGs
- Scikit-learn: https://scikit-learn.org/