程序包 weka.core.matrix

类 QRDecomposition

java.lang.Object
weka.core.matrix.QRDecomposition
所有已实现的接口:
Serializable, RevisionHandler

public class QRDecomposition extends Object implements Serializable, RevisionHandler
QR Decomposition.

For an m-by-n matrix A with m >= n, the QR decomposition is an m-by-n orthogonal matrix Q and an n-by-n upper triangular matrix R so that A = Q*R.

The QR decompostion always exists, even if the matrix does not have full rank, so the constructor will never fail. The primary use of the QR decomposition is in the least squares solution of nonsquare systems of simultaneous linear equations. This will fail if isFullRank() returns false.

Adapted from the JAMA package.

版本:
$Revision: 1.4 $
作者:
The Mathworks and NIST, Fracpete (fracpete at waikato dot ac dot nz)
另请参阅:
  • 构造器详细资料

    • QRDecomposition

      public QRDecomposition(Matrix A)
      QR Decomposition, computed by Householder reflections.
      参数:
      A - Rectangular matrix
  • 方法详细资料

    • isFullRank

      public boolean isFullRank()
      Is the matrix full rank?
      返回:
      true if R, and hence A, has full rank.
    • getH

      public Matrix getH()
      Return the Householder vectors
      返回:
      Lower trapezoidal matrix whose columns define the reflections
    • getR

      public Matrix getR()
      Return the upper triangular factor
      返回:
      R
    • getQ

      public Matrix getQ()
      Generate and return the (economy-sized) orthogonal factor
      返回:
      Q
    • solve

      public Matrix solve(Matrix B)
      Least squares solution of A*X = B
      参数:
      B - A Matrix with as many rows as A and any number of columns.
      返回:
      X that minimizes the two norm of Q*R*X-B.
      抛出:
      IllegalArgumentException - Matrix row dimensions must agree.
      RuntimeException - Matrix is rank deficient.
    • getRevision

      public String getRevision()
      Returns the revision string.
      指定者:
      getRevision 在接口中 RevisionHandler
      返回:
      the revision