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#Cern.colt.matrix.linalg Classes and Interfaces - 9 results found.
Name | Description | Type | Package | Framework |
Algebra | Linear algebraic matrix operations operating on DoubleMatrix2D; concentrates most functionality of this package. | Class | cern.colt.matrix.linalg | Colt |
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CholeskyDecomposition | For a symmetric, positive definite matrix A, the Cholesky decompositionis a lower triangular matrix L so that A = L*L'; | Class | cern.colt.matrix.linalg | Colt |
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EigenvalueDecomposition | Eigenvalues and eigenvectors of a real matrix A. | Class | cern.colt.matrix.linalg | Colt |
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LUDecomposition | For an m x n matrix A with m >= n, the LU decomposition is an m x nunit lower triangular matrix L, an n x n upper triangular matrix U, | Class | cern.colt.matrix.linalg | Colt |
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LUDecompositionQuick | A low level version of LUDecomposition, avoiding unnecessary memory allocation and copying. | Class | cern.colt.matrix.linalg | Colt |
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Matrix2DMatrix2DFunction | Interface that represents a function object: a function that takes two arguments and returns a single value. | Interface | cern.colt.matrix.linalg | Colt |
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Property | Tests matrices for linear algebraic properties (equality, tridiagonality, symmetry, singularity, etc). | Class | cern.colt.matrix.linalg | Colt |
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QRDecomposition | For an m x n matrix A with m >= n, the QR decomposition is an m x northogonal matrix Q and an n x n upper triangular matrix R so that | Class | cern.colt.matrix.linalg | Colt |
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SingularValueDecomposition | For an m x n matrix A with m >= n, the singular value decomposition isan m x n orthogonal matrix U, an n x n diagonal matrix S, and | Class | cern.colt.matrix.linalg | Colt |