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.