🎚️

Ridge & Lasso

Regression

🎚️

Ridge & Lasso

Regression

Which should you use?

L1 (Lasso) promotes sparsity by setting coefficients to zero, while L2 (Ridge) shrinks all coefficients towards zero but keeps them non-zero.

Key Differences

Factor

Ridge & Lasso

Penalty

Sum of |weights| (L1)

Sum of weights² (L2)

Sparsity

Creates zeros (feature selection)

Shrinks but no zeros

Solution

Not differentiable at 0

Smooth, closed-form

Use Case

Feature selection

Prevent overfitting

Use Ridge & Lasso when:

Feature selection needed

Expect only some features are relevant

Want sparse, interpretable model

High-dimensional data with few important features

Learn Ridge & Lasso

Use Ridge & Lasso when:

All features likely contribute

Multicollinearity present

Stable coefficient estimates needed

No need for feature selection

Learn Ridge & Lasso

Real-World Applications

Ridge & Lasso

Feature selection

High-dimensional data

Sparse models

Ridge & Lasso

Feature selection

High-dimensional data

Sparse models

Ready to learn both algorithms?

Interactive lessons with visualizations and hands-on practice

Explore ML Algorithms

🎚️

Ridge & Lasso

Regression

🎚️

Ridge & Lasso

Regression

Which should you use?

L1 (Lasso) promotes sparsity by setting coefficients to zero, while L2 (Ridge) shrinks all coefficients towards zero but keeps them non-zero.

Key Differences

Factor

Ridge & Lasso

Penalty

Sum of |weights| (L1)

Sum of weights² (L2)

Sparsity

Creates zeros (feature selection)

Shrinks but no zeros

Solution

Not differentiable at 0

Smooth, closed-form

Use Case

Feature selection

Prevent overfitting

Use Ridge & Lasso when:

Feature selection needed

Expect only some features are relevant

Want sparse, interpretable model

High-dimensional data with few important features

Learn Ridge & Lasso

Use Ridge & Lasso when:

All features likely contribute

Multicollinearity present

Stable coefficient estimates needed

No need for feature selection

Learn Ridge & Lasso

Real-World Applications

Ridge & Lasso

Feature selection

High-dimensional data

Sparse models

Ridge & Lasso

Feature selection

High-dimensional data

Sparse models

Ready to learn both algorithms?

Interactive lessons with visualizations and hands-on practice

Explore ML Algorithms