xform_function: Add a function transformation to a xform_wrap object.

In pmml: Generate PMML for Various Models

Add a function transformation to a xform_wrap object.

Description

Add a function transformation to a xform_wrap object.

Usage

xform_function(
  wrap_object,
  orig_field_name,
  new_field_name = "newField",
  new_field_data_type = "numeric",
  expression,
  map_missing_to = NA
)

Arguments

wrap_object	Output of xform_wrap or another transformation function.
orig_field_name	String specifying name(s) of the original data field(s) being used in the transformation.
new_field_name	Name of the new field created by the transformation.
new_field_data_type	R data type of the new field created by the transformation ("numeric" or "factor").
expression	String expression specifying the transformation.
map_missing_to	Value to be given to the transformed variable if the value of any input variable is missing.

Details

Calculate the expression provided in expression for every row in the wrap_object$data data frame. The expression argument must represent a valid R expression, and any functions used in expression must be defined in the current environment.

The name of the new field is optional (a default name is provided), but an error will be thrown if attempting to create a field with a name that already exists in the xform_wrap object.

When new_field_data_type = "numeric", the DerivedField attributes in PMML will be dataType = "double" and optype = "continuous". When new_field_data_type = "factor", these attributes will be dataType = "string" and optype = "categorical".

Value

R object containing the raw data, the transformed data and data statistics. The data data frame will contain a new new_field_name column, and field_data will contain a new new_field_name row.

See Also

xform_wrap

Examples

# Load the standard iris dataset:
data(iris)

# Wrap the data:
iris_box <- xform_wrap(iris)

# Perform a transform on the Sepal.Length field:
# the value is squared and then divided by 100
iris_box <- xform_function(iris_box,
  orig_field_name = "Sepal.Length",
  new_field_name = "Sepal.Length.Transformed",
  expression = "(Sepal.Length^2)/100"
)

# Combine two fields to create another new feature:
iris_box <- xform_function(iris_box,
  orig_field_name = "Sepal.Width, Petal.Width",
  new_field_name = "Width.Sum",
  expression = "Sepal.Width + Sepal.Length"
)

# Create linear model using the derived features:
fit <- lm(Petal.Length ~
Sepal.Length.Transformed + Width.Sum, data = iris_box$data)

# Create pmml from the fit:
fit_pmml <- pmml(fit, transform = iris_box)

pmml documentation built on March 18, 2022, 5:49 p.m.