ML CDOUB: Difference between revisions

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{{DISPLAYTITLE:ML_CDOUB}}
{{TAGDEF|ML_CDOUB|[real]}}
{{DEF|ML_CDOUB|4.0|for {{TAGO|ML_MODE|select}}|2.0|else}}


{{TAGDEF|ML_FF_CDOUB|[real]|2.0}}
Description: This tag controls the criterion for "enforced" DFT calculations within the machine learning force field method.
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The usage of this tag in combination with the learning algorithms is described here: [[Machine learning force field calculations: Basics#Sampling of training data and local reference configurations|here]].


Description: This flag controls the necessity of DFT calculations in the machine learning force field method
If at any time, the estimated force errors are {{TAG|ML_CDOUB}} times larger than the Bayesian threshold (i.e. "critically" high), 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_NMDINT}}).
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This flag is applied in the case of {{TAG|ML_FF_ISAMPLE}}=2. 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.


== Related Tags and Sections ==
== Related tags and articles ==
{{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_ISAMPLE}}, {{TAG|ML_FF_CSF}}, {{TAG|ML_FF_CTIFOR}}, {{TAG|ML_FF_CTIFOR}}
{{TAG|ML_LMLFF}}, {{TAG|ML_MCONF_NEW}}, {{TAG|ML_CTIFOR}}, {{TAG|ML_NMDINT}}


{{sc|ML_FF_CDOUB|Examples|Examples that use this tag}}
{{sc|ML_CDOUB|Examples|Examples that use this tag}}
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[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]]
[[Category:INCAR tag]][[Category:Machine-learned force fields]]

Latest revision as of 14:37, 19 October 2023

ML_CDOUB = [real] 

Default: ML_CDOUB = 4.0 for ML_MODE = select
= 2.0 else

Description: This tag controls the criterion for "enforced" DFT calculations within the machine learning force field method.


The usage of this tag in combination with the learning algorithms is described here: here.

If at any time, the estimated force errors are ML_CDOUB times larger than the Bayesian threshold (i.e. "critically" high), 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_NMDINT).

Related tags and articles

ML_LMLFF, ML_MCONF_NEW, ML_CTIFOR, ML_NMDINT

Examples that use this tag