Base class for Counterfactual Explanation Methods for Classification Tasks

Source: R/CounterfactualMethodClassif.R

Abstract base class for counterfactual explanation methods for classifcation tasks.

CounterfactualMethodClassif can only be initialized for classification tasks. Child classes inherit the (public) $find_counterfactuals() method, which calls a (private) $run() method. This $run() method should be implemented by the child classes and return the counterfactuals as a data.table (preferably) or a data.frame.

Inheritance

Child classes: MOCClassif, WhatIfClassif, NICEClassif

Super class

counterfactuals::CounterfactualMethod -> CounterfactualMethodClassif

Methods

Public methods

Inherited methods

Method new()

Creates a new CounterfactualMethodClassif object.

Usage

CounterfactualMethodClassif$new(
  predictor,
  lower = NULL,
  upper = NULL,
  distance_function = NULL
)

Arguments

predictor

(Predictor)
The object (created with iml::Predictor$new()) holding the machine learning model and the data.

lower

(numeric() | NULL)
Vector of minimum values for numeric features. If NULL (default), the element for each numeric feature in lower is taken as its minimum value in predictor$data$X. If not NULL, it should be named with the corresponding feature names.

upper

(numeric() | NULL)
Vector of maximum values for numeric features. If NULL (default), the element for each numeric feature in upper is taken as its maximum value in predictor$data$X. If not NULL, it should be named with the corresponding feature names.

distance_function

(function() | NULL)
A distance function that may be used by the leaf classes. If specified, the function must have three arguments: x, y, and data and return a double matrix with nrow(x) rows and nrow(y) columns.

Method find_counterfactuals()

Runs the counterfactual method and returns the counterfactuals. It searches for counterfactuals that have a predicted probability in the interval desired_prob for the desired_class.

Usage

CounterfactualMethodClassif$find_counterfactuals(
  x_interest,
  desired_class = NULL,
  desired_prob = c(0.5, 1)
)

Arguments

x_interest

(data.table(1) | data.frame(1))
A single row with the observation of interest.

desired_class

(character(1) | NULL)
The desired class. If NULL (default) then predictor$class is taken.

desired_prob

(numeric(1) | numeric(2))
The desired predicted probability of the desired_class. It can be a numeric scalar or a vector with two numeric values that specify a probability interval. For hard classification tasks this can be set to 0 or 1, respectively. A scalar is internally converted to an interval.

Returns

A Counterfactuals object containing the results.

Method clone()

The objects of this class are cloneable with this method.

Usage

CounterfactualMethodClassif$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.