ML CDOUB: Difference between revisions
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[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]] | [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] | ||
Revision as of 15:14, 29 February 2020
ML_FF_CDOUB = [real]
Default: ML_FF_CDOUB = 2.0
Description: This flag controls the necessity of DFT calculations in the machine learning force field method.
This flag is applied in the case of ML_FF_ISAMPLE=2 or 3. In that case if at any time the estimated error is ML_FF_CDOUB times larger than the threshold (ML_FF_CSF for the spilling factor and ML_FF_CTIFOR or it's updated value form ML_FF_LCRITERIA=.TRUE. for the Bayesian error), the sampling is stopped and a new force field is generated (even if the counter for sampling is below the minimum amount of sampled structures ML_FF_NMDINT).
Related Tags and Sections
ML_FF_LMLFF, ML_FF_ISAMPLE, ML_FF_CSF, ML_FF_CTIFOR, ML_FF_CTIFOR, ML_FF_IERR