org.tribuo.classification.evaluation

Interface ConfusionMatrix<T extends Classifiable<T>>

Type Parameters:

T - The type of the output.

All Known Implementing Classes:

LabelConfusionMatrix, MultiLabelConfusionMatrix

public interface ConfusionMatrix<T extends Classifiable<T>>

A confusion matrix for Classifiables.

We interpret it as follows: C[i, j] = k means "the TRUE class 'j' was PREDICTED to be class 'i' a total of 'k' times".

In other words, the row indices correspond to the model's predictions, and the column indices correspond to the ground truth.

Method Summary

Modifier and Type	Method and Description
double	confusion(T predictedLabel, T trueLabel) The number of times the supplied predicted label was returned for the supplied true class.
default double	fn() The total number of false negatives.
double	fn(T cls) The number of false negatives for the supplied label.
default double	fp() The total number of false positives.
double	fp(T cls) The number of false positives for the supplied label.
ImmutableOutputInfo<T>	getDomain() Returns the classification domain that this confusion matrix operates over.
static <T extends Classifiable<T>> double	sumOverOutputs(ImmutableOutputInfo<T> domain, ToDoubleFunction<T> getter) Sums the supplied getter over the domain.
double	support() The number of examples this confusion matrix has seen.
double	support(T cls) The number of examples with this true label this confusion matrix has seen.
default double	tn() The total number of true negatives.
double	tn(T cls) The number of true negatives for the supplied label.
default double	tp() The total number of true positives.
double	tp(T cls) The number of true positives for the supplied label.

Method Detail

getDomain

ImmutableOutputInfo<T> getDomain()

Returns the classification domain that this confusion matrix operates over.

Returns:

The classification domain.

support

double support()

The number of examples this confusion matrix has seen.

Returns:

The number of examples.

support

double support(T cls)

The number of examples with this true label this confusion matrix has seen.

Parameters:

cls - The label.

Returns:

The number of examples.

tp

double tp(T cls)

The number of true positives for the supplied label.

Parameters:

cls - The label.

Returns:

The number of examples.

fp

double fp(T cls)

The number of false positives for the supplied label.

Parameters:

cls - The label.

Returns:

The number of examples.

fn

double fn(T cls)

The number of false negatives for the supplied label.

Parameters:

cls - The label.

Returns:

The number of examples.

tn

double tn(T cls)

The number of true negatives for the supplied label.

Parameters:

cls - The label.

Returns:

The number of examples.

confusion

double confusion(T predictedLabel,
                 T trueLabel)

The number of times the supplied predicted label was returned for the supplied true class.

Parameters:

predictedLabel - The predicted label.

trueLabel - The true label.

Returns:

The number of examples predicted as predictedLabel when the true label was trueLabel.

tp

default double tp()

The total number of true positives.

Returns:

The total true positives.

fp

default double fp()

The total number of false positives.

Returns:

The total false positives.

fn

default double fn()

The total number of false negatives.

Returns:

The total false negatives.

tn

default double tn()

The total number of true negatives.

Returns:

The total true negatives.

sumOverOutputs

static <T extends Classifiable<T>> double sumOverOutputs(ImmutableOutputInfo<T> domain,
                                                         ToDoubleFunction<T> getter)

Sums the supplied getter over the domain.

Type Parameters:

T - The type of the output.

Parameters:

domain - The domain to sum over.

getter - The getter to use.

Returns:

The total summed over the domain.