Distances API Reference
Functions
ChemometricsTools.Kernel
— Method.(K::Kernel)(X)
This is a convenience function to allow for one-line construction of kernels from a Kernel object K
and new data X
.
ChemometricsTools.Kernel
— Method.Kernel(X::Array)
Default constructor for Kernel object. Returns the linear kernel of X
.
ChemometricsTools.AdjacencyMatrix
— Method.NearestNeighbors(DistanceMatrix)
Returns the nearest neighbor adjacency matrix from a given DistanceMatrix
.
ChemometricsTools.CauchyKernel
— Method.CauchyKernel(X, Y, sigma)
Creates a Cauchy kernel from Arrays X
and Y
using hyperparameters sigma
.
ChemometricsTools.CauchyKernel
— Method.CauchyKernel(X, sigma)
Creates a Cauchy kernel from Array X
using hyperparameters sigma
.
ChemometricsTools.CenterKernelMatrix
— Function.CenterKernelMatrix(X)
Returns a centered kernel matrix.
ChemometricsTools.EuclideanDistance
— Method.EuclideanDistance(X, Y)
Returns the euclidean distance matrix of X and Y such that the columns are the samples in Y.
ChemometricsTools.EuclideanDistance
— Method.EuclideanDistance(X)
Returns the Grahm aka the euclidean distance matrix of X
.
ChemometricsTools.GaussianKernel
— Method.GaussianKernel(X, Y, sigma)
Creates a Gaussian/RBF kernel from Arrays X
and Y
with hyperparameter sigma
.
ChemometricsTools.GaussianKernel
— Method.GaussianKernel(X, sigma)
Creates a Gaussian/RBF kernel from Array X
using hyperparameter sigma
.
ChemometricsTools.InClassAdjacencyMatrix
— Function.InClassAdjacencyMatrix(DistanceMatrix, YHOT, K = 1)
Computes the in class Adjacency matrix with K nearest neighbors.
ChemometricsTools.LevenshteinDistance
— Method.LevenshteinDistance(s::AbstractString, t::AbstractString)
Calculates the LevenshteinDistance aka the edit distance between 2 strings.
Borrowed from: https://rosettacode.org/wiki/Levenshtein_distance#Julia
ChemometricsTools.LinearKernel
— Method.LinearKernel(X, Y, c)
Creates a Linear kernel from Arrays X
and Y
with hyperparameter C
.
ChemometricsTools.LinearKernel
— Method.LinearKernel(X, c)
Creates a Linear kernel from Array X
and hyperparameter C
.
ChemometricsTools.ManhattanDistance
— Method.ManhattanDistance(X, Y)
Returns the Manhattan distance matrix of X and Y such that the columns are the samples in Y.
ChemometricsTools.ManhattanDistance
— Method.ManhattanDistance(X)
Returns the Manhattan distance matrix of X
.
ChemometricsTools.MinkowskiDistance
— Method.MinkowskiDistance(X, Y, p)
Returns the Minkowski distance matrix of X
and Y
using order p
such that the columns are the samples in Y
.
ChemometricsTools.MinkowskiDistance
— Method.MinkowskiDistance(X, p)
Returns the Manhattan distance matrix of X
using order p
.
ChemometricsTools.NearestNeighbors
— Method.NearestNeighbors(DistanceMatrix, N)
Returns a matrix of dimensions DistanceMatrix rows, by N columns. Basically this goes through each row and finds the ones corresponding column which has the smallest distance.
ChemometricsTools.OutOfClassAdjacencyMatrix
— Function.OutOfClassAdjacencyMatrix(DistanceMatrix, YHOT, K = 1)
Computes the out of class Adjacency matrix with K nearest neighbors.
SquareEuclideanDistance(X, Y)
Returns the squared euclidean distance matrix of X and Y such that the columns are the samples in Y.
SquareEuclideanDistance(X)
Returns the squared Grahm aka the euclidean distance matrix of X
.