Method | Description | |
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Center ( this matrix, bool inPlace = false ) : ].double[ |
Centers column data, subtracting the empirical mean from each variable.
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Center ( this matrix, double means, bool inPlace = false ) : ].double[ |
Centers column data, subtracting the empirical mean from each variable.
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Center ( this observation, double result = null ) : double[] |
Centers an observation, subtracting the empirical mean from each element in the observation vector.
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Center ( this values, double mean, double result = null ) : double[] |
Centers an observation, subtracting the empirical mean from each element in the observation vector.
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Center ( this matrix, bool inPlace = false ) : double[][] |
Centers column data, subtracting the empirical mean from each variable.
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Center ( this matrix, double means, bool inPlace = false ) : double[][] |
Centers column data, subtracting the empirical mean from each variable.
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Distance ( this kernel, double x, double y ) : double |
Computes the kernel distance for a kernel function even if it doesn't implement the Accord.Math.Distances.IDistance interface. Can be used to check the proper implementation of the distance function.
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InnerFence ( this quartiles ) : |
Creates Tukey's box plot inner fence.
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OuterFence ( this quartiles ) : |
Creates Tukey's box plot outer fence.
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RandomCovariance ( int size, double minValue, double maxValue ) : ].double[ |
Generates a random Measures.Covariance(double[], double[], bool) matrix.
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Rank ( this samples, bool alreadySorted = false ) : double[] |
Gets the rank of a sample, often used with order statistics.
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SplitInformation ( int samples, int partitions ) : double |
Computes the split information measure.
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Standardize ( this matrix, bool inPlace = false ) : ].double[ |
Standardizes column data, removing the empirical standard deviation from each variable. This method does not remove the empirical mean prior to execution. |
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Standardize ( this matrix, double standardDeviations, bool inPlace = false, double tol = 1e-12 ) : ].double[ |
Standardizes column data, removing the empirical standard deviation from each variable. This method does not remove the empirical mean prior to execution. |
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Standardize ( this values, bool inPlace = false ) : double[] |
Standardizes column data, removing the empirical standard deviation from each variable. This method does not remove the empirical mean prior to execution. |
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Standardize ( this values, double standardDeviation, bool inPlace = false ) : double[] |
Standardizes column data, removing the empirical standard deviation from each variable. This method does not remove the empirical mean prior to execution. |
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Standardize ( this matrix, bool inPlace = false ) : double[][] |
Standardizes column data, removing the empirical standard deviation from each variable. This method does not remove the empirical mean prior to execution. |
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Standardize ( this matrix, double standardDeviations, bool inPlace = false, double tol = 1e-12 ) : double[][] |
Standardizes column data, removing the empirical standard deviation from each variable. This method does not remove the empirical mean prior to execution. |
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ZScores ( this matrix ) : ].double[ |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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ZScores ( this matrix, double means, double standardDeviations ) : ].double[ |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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ZScores ( this matrix ) : double[][] |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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ZScores ( this matrix, double means, double standardDeviations ) : double[][] |
Generates the Standard Scores, also known as Z-Scores, from the given data.
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public static Center ( this matrix, bool inPlace = false ) : ].double[ | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
return | ].double[ |
public static Center ( this matrix, double means, bool inPlace = false ) : ].double[ | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
means | double | The mean value of the given values, if already known. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
return | ].double[ |
public static Center ( this observation, double result = null ) : double[] | ||
observation | this | An array of double precision floating-point numbers. |
result | double | The destination array where the result of this operation should be stored. |
return | double[] |
public static Center ( this values, double mean, double result = null ) : double[] | ||
values | this | An array of double precision floating-point numbers. |
mean | double | The mean of the |
result | double | The destination array where the result of this operation should be stored. |
return | double[] |
public static Center ( this matrix, bool inPlace = false ) : double[][] | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
return | double[][] |
public static Center ( this matrix, double means, bool inPlace = false ) : double[][] | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
means | double | The mean value of the given values, if already known. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
return | double[][] |
public static Distance ( this kernel, double x, double y ) : double | ||
kernel | this | The kernel function whose distance needs to be evaluated. |
x | double | An input point |
y | double | An input point |
return | double |
public static InnerFence ( this quartiles ) : |
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quartiles | this | |
return |
public static OuterFence ( this quartiles ) : |
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quartiles | this | |
return |
public static RandomCovariance ( int size, double minValue, double maxValue ) : ].double[ | ||
size | int | The size of the square matrix. |
minValue | double | The minimum value for a diagonal element. |
maxValue | double | The maximum size for a diagonal element. |
return | ].double[ |
public static Rank ( this samples, bool alreadySorted = false ) : double[] | ||
samples | this | |
alreadySorted | bool | |
return | double[] |
public static SplitInformation ( int samples, int partitions ) : double | ||
samples | int | The total number of samples. |
partitions | int | The partitioning. |
return | double |
public static Standardize ( this matrix, bool inPlace = false ) : ].double[ | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
return | ].double[ |
public static Standardize ( this matrix, double standardDeviations, bool inPlace = false, double tol = 1e-12 ) : ].double[ | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
standardDeviations | double | The values' standard deviation vector, if already known. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
tol | double | The minimum value that will be taken as the standard deviation in case the deviation is too close to zero. |
return | ].double[ |
public static Standardize ( this values, bool inPlace = false ) : double[] | ||
values | this | An array of double precision floating-point numbers. |
inPlace | bool | True to perform the operation in place, /// altering the original input matrix. |
return | double[] |
public static Standardize ( this values, double standardDeviation, bool inPlace = false ) : double[] | ||
values | this | An array of double precision floating-point numbers. |
standardDeviation | double | The standard deviation of the given
/// |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
return | double[] |
public static Standardize ( this matrix, bool inPlace = false ) : double[][] | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
return | double[][] |
public static Standardize ( this matrix, double standardDeviations, bool inPlace = false, double tol = 1e-12 ) : double[][] | ||
matrix | this | A matrix where each column represent a variable and each row represent a observation. |
standardDeviations | double | The values' standard deviation vector, if already known. |
inPlace | bool | True to perform the operation in place, altering the original input matrix. |
tol | double | The minimum value that will be taken as the standard deviation in case the deviation is too close to zero. |
return | double[][] |
public static ZScores ( this matrix ) : ].double[ | ||
matrix | this | A number multi-dimensional array containing the matrix values. |
return | ].double[ |
public static ZScores ( this matrix, double means, double standardDeviations ) : ].double[ | ||
matrix | this | A number multi-dimensional array containing the matrix values. |
means | double | The mean value of the given values, if already known. |
standardDeviations | double | The values' standard deviation vector, if already known. |
return | ].double[ |
public static ZScores ( this matrix ) : double[][] | ||
matrix | this | A number multi-dimensional array containing the matrix values. |
return | double[][] |
public static ZScores ( this matrix, double means, double standardDeviations ) : double[][] | ||
matrix | this | A number multi-dimensional array containing the matrix values. |
means | double | The mean value of the given values, if already known. |
standardDeviations | double | The values' standard deviation vector, if already known. |
return | double[][] |