🚀 Master Regression 2025! 🚀
| Regression Type | Explanation | Equation | Use Case Example |
|---|---|---|---|
| Simple Linear Regression | One independent variable, one dependent variable | y = β₀ + β₁·x + ε |
Predicting house price based on square footage |
| Multiple Linear Regression | Multiple independent variables | y = β₀ + β₁·x₁ + β₂·x₂ + ... + βₙ·xₙ + ε |
Forecasting sales revenue based on marketing metrics |
| Polynomial Regression | Fits a nonlinear curve using polynomial terms | y = β₀ + β₁·x + β₂·x² + ... |
Modeling population growth over time |
| Ridge Regression | Prevents overfitting by shrinking coefficients (L2) | Minimize: ∑(yᵢ - ŷᵢ)² + α∑βⱼ² |
Stock prediction with many similar features |
| Lasso Regression | Performs feature selection by shrinking some coefficients to 0 (L1) | Minimize: ∑(yᵢ - ŷᵢ)² + α∑|βⱼ| |
Detecting major factors in customer churn |
| Elastic Net | Combines Ridge and Lasso for balanced regularization | Minimize: ∑(yᵢ - ŷᵢ)² + α₁∑|βⱼ| + α₂∑βⱼ² |
Analyzing genetics with correlated predictors |
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