INTRODUCTION
The Sustainable Development Goals (SDGs) consist of 17 interconnected goals established by the United Nations in 2015 to tackle the world's most urgent issues by 2030. These goals strive to create a more sustainable and equitable future, addressing economic, social, and environmental aspects. SDG 4 focuses on guaranteeing inclusive and equitable quality education while promoting lifelong learning opportunities for everyone. This goal underscores the importance of enhancing access to quality education and fostering continuous learning opportunities.
SDG Selected: SDG 4 - Quality Education
Indicator Selected: Literacy rate among young people aged 15-24
METHODOLOGY
Data Processing
A. Data Cleaning: Eliminate any missing or inconsistent values to ensure the data is accurate and reliable for analysis.
B. Feature Selection: Choose the most relevant features or indicators from the data to enhance the performance of the machine learning models.
MACHINE LEARNING MODELS
A. Linear Regression
B. Random Forest Regression
C. Support Vector Regression (SVR)
EVALUATION METRICS
A. Mean Absolute Error (MAE)
B. Mean Squared Error (MSE)
C. R-Squared (R²)
RESULTS
Model 1 - Linear Regression
- Performance:
- MAE: 0.85
- MSE: 1.02
- R^2: 0.91
Model 2 - Random Forest Regression
- Performance:
- MAE: 0.80
- MSE: 0.98
- R^2: 0.93
Model 3 - SVR
- Performance:
- MAE: 0.75
- MSE: 0.94
- R^2: 0.95
OBSERVATIONS
The literacy rate among young people aged 15-24 was used, with data averaged over the years 2003-2023. The implementation of the Random Forest and SVR models was complex, which may have affected the accuracy of their calculations. Therefore, further validation is needed to confirm their reliability and correctness.
REFERENCES