intubate (version 1.0.0)

lars: Interfaces for lars package for data science pipelines.

Description

Interfaces to lars functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_lars(data, ...)
ntbt_cv.lars(data, ...)

Arguments

data

data frame, tibble, list, ...

...

Other arguments passed to the corresponding interfaced function.

Value

Object returned by interfaced function.

Details

Interfaces call their corresponding interfaced function.

Examples

## Not run: 
# library(intubate)
# library(magrittr)
# library(lars)
# 
# 
# library(ISLR)
# data("Hitters")
# Hitters <- na.omit(Hitters)
# 
# dta <- list(x = model.matrix(Salary ~ ., Hitters)[, -1],  ## Remove intercept
#             y = model.frame(Salary ~ ., Hitters)[, 1])
# 
# ## ntbt_lars: Fits Least Angle Regression, Lasso and Infinitesimal
# ##            Forward Stagewise regression models
# 
# ## Original function to interface
# attach(dta)
# lasso <- lars(x, y)
# plot(lasso)
# detach()
# 
# ## The interface puts data as first parameter
# lasso <- ntbt_lars(dta, x, y)
# plot(lasso)
# 
# ## so it can be used easily in a pipeline.
# dta %>%
#   ntbt_lars(x, y) %>%
#   plot()
# 
# 
# ## ntbt_cv.lars: Computes K-fold cross-validated error curve for lars
# 
# ## Original function to interface
# set.seed(1)
# attach(dta)
# cv.lars(x, y)
# detach()
# 
# ## The interface puts data as first parameter
# set.seed(1)
# ntbt_cv.lars(dta, x, y)
# 
# ## so it can be used easily in a pipeline.
# set.seed(1)
# dta %>%
#   ntbt_cv.lars(x, y)
# ## End(Not run)