Description

Using classic machine learning models to understand driving factors of happiness globally

Project goal

• Analyze the World Happiness Report to identify factors driving happiness
• Ultimately, provide actionable insights for policymakers to improve well-being globally

Installations

Check ./prerequisites for more

Methodology

1. Data Handling (./data for more)

1. Data Preprocessing
2. Feature Engineering

2. Predictive Methods (./src for more)

1. Traditional Decision Tree
2. Logistic Regression
3. K-Nearest Neighbors
4. Lasso Regression
5. Random Forest (Ensemble Method)

3. Nested Cross Validation (./src for more)

Source Code

Check ./src for more

Dataset

Check ./data for more

Results

For in-depth analysis of the outcome, go to ./src

Average KNN Accuracy: 0.9593889325990034
Average Decision Tree Accuracy: 0.938290060319958
Average Lasso Accuracy: 0.9504656311556591
Average Random Forest Accuracy: 0.9610149488591659
Average Logistic Regression Accuracy: 0.9528979805927091

==> Random Forest is the best

Key Takeaways

• Predictive analysis shows GDP, Family, Health, and Freedom as strong contributors (in that order) to happiness
• No single factor is sufficient to bring about happiness. In countries with a high happiness ranking, multiple factors (e.g., those listed above) work together in strong combination.

==> Look at top ranking countries in the Happiness Index and identify policies that relate to the aforementioned predictors

Implications

Policy

• Countries can use happiness metrics as a blueprint for relevant policies that would improving well-being create sustainable development and global well-being

Broader Impact

• Improved Global Stability: Happier nations are often healthier, more productive, and more stable politically and economically.
• Social Equity: Policies that enhance happiness often reduce inequality, fostering more inclusive societies.
• Inspiration for Developing Nations: The index serves as a framework for nations striving to improve the quality of life despite economic limitations.

Authors

Nguyen Le
Ben Bucaj
Ryan Rodriguez
Belen Ramirez