cross_validate_nd.py

RunCrossValidation(DataDict, degree_max, k_fold=10, NumCandidates=20, SymmetricDegreePerDimension=True, cores=1, save_path='/home/docs/checkouts/readthedocs.org/user_builds/mrexo/envs/latest/lib/python3.11/site-packages/mrexo', verbose=2)

Calculate the optimal number of degrees in each dimension using the k-fold cross validation (CV) method.

Parameters:

  • DataDict (dict) – The dictionary containing the data. See the output of mrexo.mle_utils_nd.InputData().

  • degree_max (int) – The maximum degree checked during degree selection.

  • k_fold (int, default=10) – The number of folds to use for cross validation.

  • NumCandidates (int, default=20) – The number of degree candidates to test.

  • SymmetricDegreePerDimension (bool, default=True) – If True, while optimizing the number of degrees, will assume the same number of degrees in each dimension (i.e. symmetric), running through NumCandidates iterations. If False, while optimizing the number of degrees it can have NumCandidates ^ NumDimensions iterations. Therefore with 20 degree candidates in 2 dimensions, there will be 400 iterations to go through!

  • cores (int, default=1) –

    The number of cores to use for parallel processing. To use all the cores in the CPU,

    set cores=cpu_count() (requires ‘#from multiprocessing import cpu_count’).

  • save_path (str, default=os.path.dirname(__file__)) – The folder name (including path) to save results in. For example, save_path = '~/mrexo_working/trial_result' will create the ‘trial_result’ folder in ‘mrexo_working’ to contain the results.

  • verbose ({0,1,2}, default=2) – Integer specifying verbosity for logging: 0 (will not log in the log file or print statements), 1 (will write log file only), or 2 (will write log file and print statements).

Returns:

deg_choose – The optimal number of degrees in each dimension, chosen by k-fold CV.

Return type:

array[int]