| Class | Description |
|---|---|
| ArithmeticMean |
Class that computes the arithmetic mean of the given column distances.
|
| DistanceSum |
Sets the overall distance to the sum of the column distances.
|
| EuclideanDistance |
Class for computation of the Euclidean distance of two vectors.
|
| ManhattanDistance |
Class for computation of the Manhattan distance of two vectors.
|
| Mathematics |
This class contains a collection of mathematical functions
like the faculty, logarithms and several trigonometric functions.
|
| MatrixOperations |
Class used to perform matrix operations, focusing on finding vector solutions
to the vector equation F(x) = 0.
|
| MeanFunction |
In this class functions for the computation of an overall distance based on
the distance values determined for each column of a table are defined.
|
| N_Metric |
An implementation of an n-metric.
|
| PearsonCorrelation |
Implementation of the Pearson correlation.
|
| QualityMeasure |
This class is the basis of various implementations of distance functions.
|
| Relative_N_Metric |
Computes the relative distance of two vectors based on the
N_Metric
distance. |
| RelativeEuclideanDistance |
Class for computation of the relative Euclidean distance of two vectors.
|
| RelativeManhattanDistance |
Class for computation of the relative Manhattan distance of two vectors.
|
| RelativeSquaredError |
An implementation of the relative squared error with a default value to avoid
division by zero.
|
| RNG |
A Random Number Generator.
|
| Exception | Description |
|---|---|
| MatrixOperations.MatrixException |
This exception is thrown when errors in the computation of matrix-related
solutions, their eigenvalues or eigenvectors.
|
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