Partitioning {fmeffects}

R6 Class representing a partitioning

Description

This is the abstract superclass for partitioning objects like PartitioningCtree and PartitioningRpart. A Partitioning contains information about feature subspaces with conditional average marginal effects (cAME) computed for ForwardMarginalEffect objects.

Public fields

object

a ForwardMarginalEffect object with results computed

method

the method for finding feature subspaces

value

the value of method

results

descriptive statistics of the resulting feature subspaces

tree

the tree representing the partitioning, a party object

tree.control

control parameters for the RP algorithm

computed

logical specifying if compute() has been run

Methods

Public methods

• Partitioning$new()

• Partitioning$compute()

• Partitioning$plot()

• Partitioning$clone()

Method new()

Create a Partitioning object

Usage

Partitioning$new(...)

Arguments

...

Partitioning cannot be initialized, only its subclasses

Method compute()

Computes the partitioning, i.e., feature subspaces with more homogeneous FMEs, for a ForwardMarginalEffect object.

Usage

Partitioning$compute()

Returns

An Partitioning object with results.

Examples

# Compute results for an arbitrary partitioning:
# subspaces$compute()

Method plot()

Plots results, i.e., a decision tree and summary statistics of the feature subspaces, for an Partitioning object after ⁠$compute()⁠ has been run.

Usage

Partitioning$plot()

Examples

# Plot an arbitrary partitioning:
# subspaces$plot()

Method clone()

The objects of this class are cloneable with this method.

Usage

Partitioning$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## ------------------------------------------------
## Method `Partitioning$compute`
## ------------------------------------------------

# Compute results for an arbitrary partitioning:
# subspaces$compute()

## ------------------------------------------------
## Method `Partitioning$plot`
## ------------------------------------------------

# Plot an arbitrary partitioning:
# subspaces$plot()