ML CDOUB: Difference between revisions
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== Related Tags and Sections == | == Related Tags and Sections == | ||
{{TAG|ML_FF_ISAMPLE}}, {{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_CSF}}, {{TAG|ML_FF_CTIFOR}}, {{TAG|ML_FF_IERR}}, {{TAG|ML_FF_NMDINT}} | |||
{{sc|ML_FF_CDOUB|Examples|Examples that use this tag}} | {{sc|ML_FF_CDOUB|Examples|Examples that use this tag}} | ||
Revision as of 07:39, 5 October 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 only if ML_FF_ISAMPLE=2 or 3. If at any time the estimated errors are ML_FF_CDOUB times larger than the Bayesian threshold ML_FF_CTIFOR or the threshold for the spilling factor ML_FF_CSF, a first principles calculations is performed and a new force field is immediately generated (even if the counter for sampling is below the minimum amount of sampled structures ML_FF_NMDINT). For details, refer to ML_FF_ISAMPLE.
Related Tags and Sections
ML_FF_ISAMPLE, ML_FF_LMLFF, ML_FF_CSF, ML_FF_CTIFOR, ML_FF_IERR, ML_FF_NMDINT