| weka.core.matrix |
|
| Java Source File Name | Type | Comment |
| CholeskyDecomposition.java | Class | Cholesky Decomposition. |
| DoubleVector.java | Class | A vector specialized on doubles. |
| EigenvalueDecomposition.java | Class | Eigenvalues and eigenvectors of a real matrix. |
| ExponentialFormat.java | Class | |
| FlexibleDecimalFormat.java | Class | |
| FloatingPointFormat.java | Class | |
| IntVector.java | Class | A vector specialized on integers. |
| LinearRegression.java | Class | Class for performing (ridged) linear regression. |
| LUDecomposition.java | Class | LU Decomposition.
For an m-by-n matrix A with m >= n, the LU decomposition is an m-by-n
unit lower triangular matrix L, an n-by-n upper triangular matrix U, and a
permutation vector piv of length m so that A(piv,:) = L*U. |
| Maths.java | Class | Utility class. |
| Matrix.java | Class | Jama = Java Matrix class.
The Java Matrix Class provides the fundamental operations of numerical linear
algebra. |
| QRDecomposition.java | Class | 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. |
| SingularValueDecomposition.java | Class | 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] >= ... |