BinaryConfusionMatrix Class |
Namespace: FinMath.MachineLearning
[SerializableAttribute] public class BinaryConfusionMatrix
The BinaryConfusionMatrix type exposes the following members.
Name | Description | |
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![]() | BinaryConfusionMatrix | Initializes a new instance of the BinaryConfusionMatrix class |
Name | Description | |
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![]() | Accuracy |
The ratio between correct predictions and the total number of tests.
http://en.wikipedia.org/wiki/Confusion_matrix
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![]() | DiagnosticOddsRatio |
The diagnostic odds ratio is a measure of the effectiveness of a test.
http://en.wikipedia.org/wiki/Confusion_matrix
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![]() | F1 |
The harmonic average of the Precision and Recall.
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | FallOut |
The ratio between the number of negative events wrongly categorized as positive and the total number of actual negative events (aka @see FalsePositiveRate).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | FalseDiscoveryRate |
The ratio between the number of negative events wrongly categorized as positive and the total number of positive predictions.
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | FalseNegative |
Number of positive values incorrectly predicted as negative (miss).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | FalseNegativeRate |
The ratio between the number of positive events wrongly categorized as negative and the total number of actual positive events (aka @see MissRate).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | FalseOmissionRate |
The ratio between the number of positive events wrongly categorized as negative and the total number of negative predictions.
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | FalsePositive |
Number of negative values incorrectly predicted as positive (false alarm).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | FalsePositiveRate |
The ratio between the number of negative events wrongly categorized as positive and the total number of actual negative events (aka @see FallOut).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | MatthewsCorrelationCoefficient |
The Matthews correlation coefficient.
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | MissRate |
The ratio between the number of positive events wrongly categorized as negative and the total number of actual positive events (aka @see FalseNegativeRate).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | NegativeLikelihoodRatio |
The probability of miss (@see FalseNegativeRate) divided by the probability of correct negative prediction (@see TrueNegativeRate).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | NegativePredictiveValue |
The proportion of negative predictions that are true negative.
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | PositiveLikelihoodRatio |
The probability of detection (@see TruePositiveRate) divided by the probability of false alarm (@see TrueNegativeRate).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | PositivePredictiveValue |
The proportion of positive predictions that are true positive (aka @see Precision).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | Precision |
The proportion of positive predictions that are true positive (aka @see PositivePredictiveValue).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | Recall |
The proportion of actual positives that are correctly identified as such (aka @see TruePositiveRate, @see Sensitivity, or probability of detection).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | Selectivity |
The proportion of actual negatives that are correctly identified as such (aka @see TrueNegativeRate, @see Specificity).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | Sensitivity |
The proportion of actual positives that are correctly identified as such (aka @see TruePositiveRate, @see Recall, or probability of detection).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | Specificity |
The proportion of actual negatives that are correctly identified as such (aka @see TrueNegativeRate, @see Selectivity).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | TrueNegative |
Number of correctly predicted negative values.
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | TrueNegativeRate |
The proportion of actual negatives that are correctly identified as such (aka @see Specificity, @see Selectivity).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | TruePositive |
Number of correctly predicted positive values.
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | TruePositiveRate |
The proportion of actual positives that are correctly identified as such (aka @see Sensitivity, @see Recall, or probability of detection).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | TypeIError |
Number of negative values incorrectly predicted as positive (false alarm).
http://en.wikipedia.org/wiki/Confusion_matrix
|
![]() | TypeIIError |
Number of positive values incorrectly predicted as negative (miss).
http://en.wikipedia.org/wiki/Confusion_matrix
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Name | Description | |
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![]() | Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) |
![]() | GetHashCode | Serves as the default hash function. (Inherited from Object.) |
![]() | GetType | Gets the Type of the current instance. (Inherited from Object.) |
![]() | ToString | Returns a string that represents the current object. (Inherited from Object.) |
![]() | Update(Boolean, Boolean) |
Update confusion matrix form two observations
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![]() | Update(IEnumerable<Boolean>, IEnumerable<Boolean>) |
Update confusion matrix from the data sequences
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![]() | Update<T>(IEnumerable<Boolean>, IEnumerable<T>, Func<T, Boolean>) |
Update confusion matrix from the data sequences
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