ML CDOUB: Difference between revisions
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Description: This flag controls the necessity of DFT calculations in the machine learning force field method. | Description: This flag controls the necessity of DFT calculations in the machine learning force field method. | ||
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If at any time, the estimated errors are {{TAG|ML_FF_CDOUB}} times larger than the Bayesian threshold, a first principles calculation is performed and a new force field is immediately generated (even if the counter for sampling is below the minimum amount of sampled structures {{TAG|ML_FF_NMDINT}}). For details, refer to {{TAG|ML_FF_ISAMPLE}}. | |||
== Related Tags and Sections == | == Related Tags and Sections == | ||
{{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_CTIFOR}}, {{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 10:02, 12 June 2021
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.
If at any time, the estimated errors are ML_FF_CDOUB times larger than the Bayesian threshold, a first principles calculation 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_LMLFF, ML_FF_CTIFOR, ML_FF_NMDINT