adapt_rank
Activate adaptive procedure for determining best rank representation
Specification
Alias: None
Arguments: None
Default: false
Description
The adaptive algorithm proceeds as follows:
-Start from rank start_rank
and form an approximation
-Adapt the current approximation by searching for a solution with lower rank that achieves L2 accuracy within epsilon tolerance of the reference.
-If a lower rank solution is found with comparable accuracy, then stop. If not, increase the rank by an amount specified by kick_rank
.
-Return to step 2 and continue until either max_rank
is reached or a converged rank (rank less than current reference with comparable accuracy) is found.
Default Behavior
No cross validation for rank.
Examples
This example shows specification of a rank adaptation starting at rank 2, incrementing by 2, and limited at rank 10.
model,
id_model = 'FT'
surrogate global function_train
start_order = 5
adapt_rank start_rank = 2 kick_rank = 2 max_rank = 10
solver_tolerance = 1e-12
rounding_tolerance = 1e-12
dace_method_pointer = 'SAMPLING'
Note that adapt_rank
and adapt_order
can either be combined or
used separately.