[−][src]Module easy_ml::linear_algebra
Linear algebra algorithms on numbers and matrices
Note that these functions are also exposed as corresponding methods on the Matrix type, but in depth documentation is only presented here.
It is recommended to favor the corresponding methods on the Matrix type as the Rust compiler can get confused with the generics on these functions if you use these methods without turbofish syntax.
Functions
cholesky_decomposition | Computes the cholesky decomposition of a matrix. This yields a matrix |
covariance_column_features | Computes the covariance matrix for an NxM feature matrix, in which each N'th row has M features to find the covariance and variance of. |
covariance_row_features | Computes the covariance matrix for an NxM feature matrix, in which each M'th column has N features to find the covariance and variance of. |
determinant | Computes the determinant of a square matrix. For a 2 x 2 matrix this is given by
|
inverse | Computes the inverse of a matrix provided that it exists. To have an inverse a matrix must be square (same number of rows and columns) and it must also have a non zero determinant. |