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java.lang.Objectweka.core.matrix.SingularValueDecomposition
public class SingularValueDecomposition
Singular Value Decomposition.
For an m-by-n matrix A with m >= n, the singular value decomposition is an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and an n-by-n orthogonal matrix V so that A = U*S*V'.
The singular values, sigma[k] = S[k][k], are ordered so that sigma[0] >= sigma[1] >= ... >= sigma[n-1].
The singular value decompostion always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.
Adapted from the JAMA package.
Constructor Summary | |
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SingularValueDecomposition(Matrix Arg)
Construct the singular value decomposition |
Method Summary | |
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double |
cond()
Two norm condition number |
java.lang.String |
getRevision()
Returns the revision string. |
Matrix |
getS()
Return the diagonal matrix of singular values |
double[] |
getSingularValues()
Return the one-dimensional array of singular values |
Matrix |
getU()
Return the left singular vectors |
Matrix |
getV()
Return the right singular vectors |
double |
norm2()
Two norm |
int |
rank()
Effective numerical matrix rank |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public SingularValueDecomposition(Matrix Arg)
Arg
- Rectangular matrixMethod Detail |
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public Matrix getU()
public Matrix getV()
public double[] getSingularValues()
public Matrix getS()
public double norm2()
public double cond()
public int rank()
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
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