Tools Class |
Namespace: Accord.Statistics
The Tools type exposes the following members.
Name | Description | |
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Center(Double, Boolean) |
Centers column data, subtracting the empirical mean from each variable.
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Center(Double, Double) |
Centers an observation, subtracting the empirical
mean from each element in the observation vector.
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Center(Double, Boolean) |
Centers column data, subtracting the empirical mean from each variable.
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Center(Double, Double, Boolean) |
Centers column data, subtracting the empirical mean from each variable.
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Center(Double, Double, Double) |
Centers an observation, subtracting the empirical
mean from each element in the observation vector.
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Center(Double, Double, Boolean) | Centers column data, subtracting the empirical mean from each variable. | |
Determination |
Gets the coefficient of determination, as known as the R-Squared (R²)
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Distance |
Computes the kernel distance for a kernel function even if it doesn't
implement the IDistance interface. Can be used to check
the proper implementation of the distance function.
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Expand(Int32) | Obsolete.
Obsolete. Please use OneHot(Int32) instead.
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Expand(Int32, Int32) | Obsolete.
Obsolete. Please use OneHot(Int32) instead.
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Expand(Int32, Double, Double) | Obsolete.
Obsolete. Please use OneHot(Int32) instead.
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Expand(Int32, Int32, Int32) | Obsolete.
Obsolete. Please use Expand(Int32, Int32, Int32) instead.
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Expand(Int32, Int32, Double, Double) | Obsolete.
Obsolete. Please use OneHot(Int32) instead.
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Expand(Int32, Int32, Int32, Int32) | Obsolete.
Obsolete. Please use Expand(Int32, Int32, Int32) instead.
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FitTDistribution(Double, Double) |
Creates a new distribution that has been fit to a given set of observations.
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FitTDistribution(Double, Double) |
Creates a new distribution that has been fit to a given set of observations.
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FitTDistribution, TOptions(Double, TOptions, Double) |
Creates a new distribution that has been fit to a given set of observations.
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FitTDistribution, TOptions(Double, TOptions, Double) |
Creates a new distribution that has been fit to a given set of observations.
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FitNewTDistribution, TObservations(TDistribution, TObservations, Double) |
Creates a new distribution that has been fit to a given set of observations.
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FitNewTDistribution, TObservations, TOptions(TDistribution, TObservations, TOptions, Double) |
Creates a new distribution that has been fit to a given set of observations.
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Group | Obsolete.
Obsolete. Please use Summarize(Int32, Int32, Int32) instead.
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InnerFence |
Creates Tukey's box plot inner fence.
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OuterFence |
Creates Tukey's box plot outer fence.
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Proportions(Int32, Int32) | Obsolete.
Obsolete. Please use GetRatio(Int32, Int32) instead.
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Proportions(Int32, Int32, Int32) | Obsolete.
Obsolete. Please use GetRatio(Int32, Int32, Int32) instead.
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Random | Obsolete.
Obsolete. Please use Sample(Int32) instead.
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RandomCovariance |
Generates a random Covariance(Double, Double, Boolean) matrix.
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RandomGroups(Int32, Double) | Obsolete.
Obsolete. Please use Random(Int32, Double) instead.
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RandomGroups(Int32, Int32) | Obsolete.
Obsolete. Please use Random(Int32, Int32) instead.
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RandomGroups(Int32, Int32, Int32) | Obsolete.
Obsolete. Please use Random(Int32, Int32, Int32) instead.
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RandomSample | Obsolete.
Obsolete. Please use Sample(Int32, Int32) instead.
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Rank(Double, Boolean, Boolean) |
Gets the rank of a sample, often used with order statistics.
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Rank(Double, Boolean, Boolean, Boolean) |
Gets the rank of a sample, often used with order statistics.
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ShuffleT(IListT) | Obsolete.
Obsolete. Please use ShuffleT(IListT) instead.
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ShuffleT(T) | Obsolete.
Obsolete. Please use ShuffleT(T) instead.
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Standardize(Double, Boolean) |
Standardizes column data, removing the empirical standard deviation from each variable.
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Standardize(Double, Boolean) |
Standardizes column data, removing the empirical standard deviation from each variable.
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Standardize(Double, Boolean) |
Standardizes column data, removing the empirical standard deviation from each variable.
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Standardize(Double, Double, Boolean) |
Standardizes column data, removing the empirical standard deviation from each variable.
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Standardize(Double, Double, Boolean, Double) |
Standardizes column data, removing the empirical standard deviation from each variable.
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Standardize(Double, Double, Boolean, Double) |
Standardizes column data, removing the empirical standard deviation from each variable.
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Ties(Double) |
Gets the number of ties and distinct elements in a rank vector.
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Ties(Double, SortedDictionaryDouble, Int32) |
Gets the number of ties and distinct elements in a rank vector.
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Whitening(Double, Double) |
Computes the whitening transform for the given data, making
its covariance matrix equals the identity matrix.
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Whitening(Double, Double) |
Computes the whitening transform for the given data, making
its covariance matrix equals the identity matrix.
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ZScores(Double) |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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ZScores(Double) |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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ZScores(Double, Double, Double) |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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ZScores(Double, Double, Double) |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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