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 that case if the estimated error is {{TAG|ML_FF_CDOUB}} times larger than the threshold ({{TAG|ML_FF_CSF}} for the spilling factor and {{TAG|ML_FF_CTIFOR}} or it's updated value form {{TAG|ML_FF_LCRITERIA}}=''.TRUE.'' for the Bayesian error), the sampling is stopped and a new force field is generated. | This flag is applied in the case of {{TAG|ML_FF_ISAMPLE}}=2 or 3. In that case if at any time the estimated error is {{TAG|ML_FF_CDOUB}} times larger than the threshold ({{TAG|ML_FF_CSF}} for the spilling factor and {{TAG|ML_FF_CTIFOR}} or it's updated value form {{TAG|ML_FF_LCRITERIA}}=''.TRUE.'' for the Bayesian error), the sampling is stopped and a new force field is generated. | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
Revision as of 10:28, 11 June 2019
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.
Related Tags and Sections
ML_FF_LMLFF, ML_FF_ISAMPLE, ML_FF_CSF, ML_FF_CTIFOR, ML_FF_CTIFOR, ML_FF_IERR