pipeliner (version 0.1.1)

transform_features: Transform machine learning feature variables

Description

A function that takes as its arguement another function defining a set of feature variable transformations, and wraps (or adapts) it for use within a machine learning pipeline.

Usage

transform_features(.f)

Arguments

.f

A unary function of a data.frame that returns a new data.frame containing only the transformed feature variables. An error will be thrown if this is not the case.

Value

A unary function of a data.frame that returns the input data.frame with the transformed feature variable columns appended. This function is assigned the classes "transform_features" and "ml_pipeline_section".

Examples

data <- head(faithful)
f <- transform_features(function(df) {
  data.frame(x1 = (df$waiting - mean(df$waiting)) / sd(df$waiting))
})

f(data)
#    eruptions waiting         x1
#  1     3.600      79  0.8324308
#  2     1.800      54 -1.0885633
#  3     3.333      74  0.4482320
#  4     2.283      62 -0.4738452
#  5     4.533      85  1.2934694
#  6     2.883      55 -1.0117236