This repo implements Ridge Regression (L2 regularisation) using pure NumPy and Matrix Algebra to analyse the dataset. The goal is to demonstrate how regularization stabilizes a linear model when features (like GDP and Life Expectancy) are highly correlated, preventing "exploding" weights.
Unlike standard implementations, this project uses the Normal Equation derived from linear algebra:
Each feature is Z-Score normalized to ensure the penalty is applied fairly across all features.
The World Happiness Report is a landmark survey of the state of global happiness that ranks 150+ countries by how happy their citizens perceive themselves to be.
The dataset is primarily based on the Cantril Ladder question: Respondents are asked to imagine a ladder, with the best possible life for them being a 10 and the worst possible life being a 0.