3 Examples

9.2

Racket

3 Examples🔗ℹ

Each example below is a literate program: the prose and the code you see are the same source that lives in the package’s "glmnet/examples/" directory and is exercised by the test suite under "glmnet/examples/test/". Every example provides a run-example thunk, so you can run any of them directly or read them as documentation that is guaranteed to stay in sync with the code.

3.1 Ordinary least squares (λ = 0)

3.2 Ridge regression (L2, α = 0)

3.3 Lasso (L1, α = 1)

3.4 Elastic net (0 < α < 1)

3.5 Binomial logistic regression (classification)

3.6 Multinomial classification (K classes)

3.7 Cox proportional hazards (survival)

3.8 Poisson regression (counts)

3.9 Multi-response Gaussian (grouped)

1	Getting started
2	User guide
3	Examples
4	API reference

3.1	Ordinary least squares (λ = 0)
3.2	Ridge regression (L2, α = 0)
3.3	Lasso (L1, α = 1)
3.4	Elastic net (0 < α < 1)
3.5	Binomial logistic regression (classification)
3.6	Multinomial classification (K classes)
3.7	Cox proportional hazards (survival)
3.8	Poisson regression (counts)
3.9	Multi-response Gaussian (grouped)