LassoPath: LASSO path for the penalized logistic regression

In tools4uplift: Tools for Uplift Modeling

Description

Fit an interaction uplift model via penalized maximum likelihood. The regularization path is computed for the lasso penalty at a grid of values for the regularization constant.

Usage

LassoPath(data, formula)

Arguments

data	a data frame containing the treatment, the outcome and the predictors.
formula	an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.

Value

a dataframe containing the coefficients values and the number of nonzeros coefficients for different values of lambda.

Author(s)

Mouloud Belbahri

References

Friedman, J., Hastie, T. and Tibshirani, R. (2010) Regularization Paths for Generalized Linear Models via Coordinate Descent, Journal of Statistical Software, Vol. 33(1), 1-22

See Also

BestFeatures, glmnet

Examples

#See glmnet() from library("glmnet") for more information

Example output

tools4uplift documentation built on Jan. 6, 2021, 5:09 p.m.