gov.sandia.cognition.learning.performance.categorization

Class AbstractBinaryConfusionMatrix

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix<java.lang.Boolean>

gov.sandia.cognition.learning.performance.categorization.AbstractBinaryConfusionMatrix

All Implemented Interfaces:

BinaryConfusionMatrix, ConfusionMatrix<java.lang.Boolean>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

DefaultBinaryConfusionMatrix

public abstract class AbstractBinaryConfusionMatrix
extends AbstractConfusionMatrix<java.lang.Boolean>
implements BinaryConfusionMatrix

An abstract implementation of the BinaryConfusionMatrix interface. Takes care of a lot of the general operations from the interface so that extending classes only need to focus on the data structure implementation.

Since:

3.1

Author:

Justin Basilico

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AbstractBinaryConfusionMatrix() Creates a new AbstractBinaryConfusionMatrix.

Method Summary

Modifier and Type	Method and Description
java.util.Set<java.lang.Boolean>	getActualCategories() Gets the set of all the actual categories.
double	getActualCount(java.lang.Boolean target) Gets the total number of entries for the given actual category.
java.util.Set<java.lang.Boolean>	getCategories() Gets the set of all categories in the confusion matrix.
double	getCount(java.lang.Boolean target, java.lang.Boolean estimate) Gets the entry in the matrix for the given actual and predicted categories, which is the count of the number of times the predicted category was given for the given actual category.
double	getFalseNegativesFraction() Gets the fraction of false negatives.
double	getFalsePositivesFraction() Gets the fraction of false positives.
double	getFScore() The F-score of the confusion matrix, which is also known as the F1-score or F-measure.
double	getFScore(double beta) The F-score for the confusion matrix with the given trade-off parameter (beta).
double	getPrecision() The precision value for the confusion matrix.
java.util.Set<java.lang.Boolean>	getPredictedCategories() Gets the set of all the predicted categories.
java.util.Set<java.lang.Boolean>	getPredictedCategories(java.lang.Boolean target) Gets the predicted categories for a given actual category.
double	getRecall() The recall value for the confusion matrix.
double	getSensitivity() The sensitivity value for the confusion matrix.
double	getSpecificity() The specificity value for the confusion matrix.
double	getTrueNegativesFraction() Gets the fraction of true negatives.
double	getTruePositivesFraction() Gets the fraction of true positives.

Methods inherited from class gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix

add, addAll, getAccuracy, getAverageCategoryAccuracy, getAverageCategoryErrorRate, getCategoryAccuracy, getCategoryErrorRate, getErrorRate, getPredictedCount, getTotalCorrectCount, getTotalCount, getTotalIncorrectCount, isEmpty

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.learning.performance.categorization.BinaryConfusionMatrix

getFalseNegativesCount, getFalsePositivesCount, getTrueNegativesCount, getTruePositivesCount

Methods inherited from interface gov.sandia.cognition.learning.performance.categorization.ConfusionMatrix

add, add, addAll, clear, getAccuracy, getAverageCategoryAccuracy, getAverageCategoryErrorRate, getCategoryAccuracy, getCategoryErrorRate, getErrorRate, getPredictedCount, getTotalCorrectCount, getTotalCount, getTotalIncorrectCount, isEmpty

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Constructor Detail

AbstractBinaryConfusionMatrix

public AbstractBinaryConfusionMatrix()

Creates a new AbstractBinaryConfusionMatrix.

Method Detail

getCategories

public java.util.Set<java.lang.Boolean> getCategories()

Description copied from interface: ConfusionMatrix

Gets the set of all categories in the confusion matrix. It is the union of the predicted and actual categories.

Specified by:

getCategories in interface ConfusionMatrix<java.lang.Boolean>

Returns:

The set of all categories.

getActualCategories

public java.util.Set<java.lang.Boolean> getActualCategories()

Description copied from interface: ConfusionMatrix

Gets the set of all the actual categories.

Specified by:

getActualCategories in interface ConfusionMatrix<java.lang.Boolean>

Returns:

The set of all actual categories.

getPredictedCategories

public java.util.Set<java.lang.Boolean> getPredictedCategories()

Description copied from interface: ConfusionMatrix

Gets the set of all the predicted categories.

Specified by:

getPredictedCategories in interface ConfusionMatrix<java.lang.Boolean>

Returns:

The set of all predicted categories.

getPredictedCategories

public java.util.Set<java.lang.Boolean> getPredictedCategories(java.lang.Boolean target)

Description copied from interface: ConfusionMatrix

Gets the predicted categories for a given actual category. This can be either a sparse set (non-zero values) or a dense set (zeros allowed). However, the sparse set will usually yield higher performance in most use cases.

Specified by:

getPredictedCategories in interface ConfusionMatrix<java.lang.Boolean>

Parameters:

target - The actual category to get the set of prediction categories for.

Returns:

The set of predicted categories for the given actual categories.

getCount

public double getCount(java.lang.Boolean target,
                       java.lang.Boolean estimate)

Description copied from interface: ConfusionMatrix

Gets the entry in the matrix for the given actual and predicted categories, which is the count of the number of times the predicted category was given for the given actual category.

Specified by:

getCount in interface ConfusionMatrix<java.lang.Boolean>

Parameters:

target - The actual category.

estimate - The predicted category.

Returns:

The count for (actual, predicted).

getActualCount

public double getActualCount(java.lang.Boolean target)

Description copied from interface: ConfusionMatrix

Gets the total number of entries for the given actual category.

Specified by:

getActualCount in interface ConfusionMatrix<java.lang.Boolean>

Overrides:

getActualCount in class AbstractConfusionMatrix<java.lang.Boolean>

Parameters:

target - The actual category.

Returns:

The total number of instances of the given actual category.

getTruePositivesFraction

public double getTruePositivesFraction()

Description copied from interface: BinaryConfusionMatrix

Gets the fraction of true positives. This is the (true, true) fraction.

Specified by:

getTruePositivesFraction in interface BinaryConfusionMatrix

Returns:

The fraction of true positives.

getFalsePositivesFraction

public double getFalsePositivesFraction()

Description copied from interface: BinaryConfusionMatrix

Gets the fraction of false positives. This is the (false, true) fraction.

Specified by:

getFalsePositivesFraction in interface BinaryConfusionMatrix

Returns:

The fraction of false positives.

getTrueNegativesFraction

public double getTrueNegativesFraction()

Description copied from interface: BinaryConfusionMatrix

Gets the fraction of true negatives. This is the (false, false) fraction.

Specified by:

getTrueNegativesFraction in interface BinaryConfusionMatrix

Returns:

The fraction of true negatives.

getFalseNegativesFraction

public double getFalseNegativesFraction()

Description copied from interface: BinaryConfusionMatrix

Gets the fraction of false negatives. This is the (true, false) fraction.

Specified by:

getFalseNegativesFraction in interface BinaryConfusionMatrix

Returns:

The fraction of false negatives.

getSensitivity

public double getSensitivity()

Description copied from interface: BinaryConfusionMatrix

The sensitivity value for the confusion matrix. The sensitivity is the number of true positives divided by the number of true positives plus the number of false negatives: TP / (TP + FN). It is equivalent to recall.

Specified by:

getSensitivity in interface BinaryConfusionMatrix

Returns:

The sensitivity, which is between 0.0 and 1.0.

getSpecificity

public double getSpecificity()

Description copied from interface: BinaryConfusionMatrix

The specificity value for the confusion matrix. The specificity is the number of true negatives divided by the number of true negatives plus the number of false positives: TN / (TN + FP).

Specified by:

getSpecificity in interface BinaryConfusionMatrix

Returns:

The specificity value, which is between 0.0 and 1.0.

getPrecision

public double getPrecision()

Description copied from interface: BinaryConfusionMatrix

The precision value for the confusion matrix. The precision is the number of true positives divided by the number of true positives plus the number of false positives: TP / (TP + FP).

Specified by:

getPrecision in interface BinaryConfusionMatrix

Returns:

The precision value, which is between 0.0 and 1.0.

getRecall

public double getRecall()

Description copied from interface: BinaryConfusionMatrix

The recall value for the confusion matrix. The recall is the number of true positives divided by the number of true positives plus the number of false negatives: TP / (TP + FN). It is equivalent to sensitivity.

Specified by:

getRecall in interface BinaryConfusionMatrix

Returns:

The recall value, which is be between 0.0 and 1.0.

getFScore

public double getFScore()

Description copied from interface: BinaryConfusionMatrix

The F-score of the confusion matrix, which is also known as the F1-score or F-measure. It is calculated as: 2 * (precision * recall) / (precision + recall) It is equivalent to the F-score with beta = 1.

Specified by:

getFScore in interface BinaryConfusionMatrix

Returns:

The F-score, which is between 0.0 and 1.0.

getFScore

public double getFScore(double beta)

Description copied from interface: BinaryConfusionMatrix

The F-score for the confusion matrix with the given trade-off parameter (beta). It is calculated as: (1 + beta^2) * (precision * recall) / ((beta^2 * precision) + recall)

Specified by:

getFScore in interface BinaryConfusionMatrix

Parameters:

beta - The beta value of the score. It is the importance assigned to precision as compared to recall.

Returns:

The F-score for the matrix, which is greater than zero.