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Least angle regression

Source: R/lars-baritsu.R
details_lars_baritsu.Rd

lars() defines a model that can predict numeric values from predictors using linear_regression(), a wrapper of mlpack::lars().

mlpack::lars() is an implementation of Least Angle Regression (Stagewise/laSso), also known as LARS.

Usage

lars(
  mode = "regression",
  engine = "baritsu",
  penalty_L1 = NULL,
  penalty_L2 = NULL
)

Arguments

mode

A single character string for the type of model. The only possible value for this model is "regression".

engine

A single character string specifying what computational engine to use for fitting.

penalty_L1

Regularization parameter for L1-norm penalty.

penalty_L2

Regularization parameter for L2-norm penalty.

Details

For this model, there is a single mode: regression

Tuning Parameters

This model has 2 tuning parameters:

  • penalty_L1 Amount of regularization for Lasso Penalty (type: double)

  • penalty_L2 Amount of regularization for Ridge Penalty (type: double)

See also

linear_regression()