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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This flag is applied in the case of {{TAG|ML_FF_ISAMPLE}}=2 or 3. In | This flag is applied in the case of {{TAG|ML_FF_ISAMPLE}}=2 or 3. In thus case, if at any time the estimated error is {{TAG|ML_FF_CDOUB}} times larger than the Bayesian threshold {{TAG|ML_FF_CTIFOR}} or ({{TAG|ML_FF_CSF}} for the spilling factor, 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 {{TAG|ML_FF_NMDINT}}). For details, refer to {{TAG|ML_FF_ISAMPLE}}. | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
{{TAG| | {{TAG|ML_FF_ISAMPLE}}, {{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_CSF}}, {{TAG|ML_FF_CTIFOR}}, {{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 07:37, 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 in the case of ML_FF_ISAMPLE=2 or 3. In thus case, if at any time the estimated error is ML_FF_CDOUB times larger than the Bayesian threshold ML_FF_CTIFOR or (ML_FF_CSF for the spilling factor, 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_CTIFOR, ML_FF_IERR, ML_FF_NMDINT