PlainSolver

class PlainSolver(options=None)

Solve the l2-norm ordinary least-squares problem without any regularization, i.e.,

min_{X} ||AX - B||_F^2.

The solution is calculated using scipy.linalg.lstsq().

Properties

A	Left-hand side data matrix.
B	"Right-hand side matrix B = [ b_1 | .
d	Number of unknowns to learn in each problem (number of columns of A).
k	Number of equations in the least-squares problem (number of rows of A).
r	Number of independent least-squares problems (number of columns of B).

Methods

cond	Calculate the 2-norm condition number of the data matrix A.
fit	Verify dimensions and save A and B.
misfit	Calculate the data misfit (residual) of the non-regularized problem for each column of B = [ b_1 | .
predict	Solve the least-squares problem.