estimate_model {pipeliner} | R Documentation |
Estimate machine learning model
Description
A function that takes as its arguement another function defining how a machine learning model should be estimated based on the variables available in the input data frame. This function is wrapped (or adapted) for use within a machine learning pipeline.
Usage
estimate_model(.f)
Arguments
.f |
A unary function of a data.frame that returns a fitted model object, which must have
a |
Value
A unary function of a data.frame that returns a fitted model object that has a
predict.{model-class}
defined This function is assigned the classes
"estimate_model"
and "ml_pipeline_section"
.
Examples
data <- head(faithful)
f <- estimate_model(function(df) {
lm(eruptions ~ 1 + waiting, df)
})
f(data)
# Call:
# lm(formula = eruptions ~ 1 + waiting, data = df)
#
# Coefficients:
# (Intercept) waiting
# -1.53317 0.06756
[Package pipeliner version 0.1.1 Index]