L2SolverDecoupled

class L2SolverDecoupled(regularizer)

Solve r independent l2-norm ordinary least-squares problems, each with the same data matrix A but different L2 regularizations λ_i > 0 for the columns of X and B:

min_{x_i} ||Ax_i - b_i||_2^2 + ||λ_i x_i||_2^2, i = 1, …, r.

The solution is calculated using the singular value decomposition of A.

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).
regularizer	Regularization scalar, matrix, or list of these.

Methods

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