ML CSIG: Difference between revisions

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{{DISPLAYTITLE:ML_CSIG}}
{{TAGDEF|ML_CSIG|[real]|<math>0.4</math>}}


{{TAGDEF|ML_FF_CSIG|[real]|<math>0.4</math>}}
Description: Parameter used in the automatic determination of threshold {{TAG|ML_CTIFOR}} for Bayesian error estimation in 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#Threshold for error of forces|here]].


Description: Parameter used in the automatic determination of threshold {{TAG|ML_FF_CTIFOR}} for Bayesian error estimation in the machine learning force field method.
The standard error of the history of maximum Bayesian errors of the forces ({{TAG|ML_MHIS}}) and it's slope must be below {{TAG|ML_CSIG}} and {{TAG|ML_CSLOPE}} so that an update of the threshold for the maximum Bayesian error of forces {{TAG|ML_CTIFOR}} can take place.  
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For details please read entry {{TAG|ML_FF_LCRITERIA}} first. The parameter {{TAG|ML_FF_CTIFOR}} is only updated, if the standard error of the collected Bayesian errors is below {{TAG|ML_FF_CSIG}} times the mean of the collected Bayesian errors.


== Related Tags and Sections ==
== Related tags and articles ==
{{TAG|ML_FF_LMLFF}}, {{TAG|ML_FF_IERR}}, {{TAG|ML_FF_ISAMPLE}}, {{TAG|ML_FF_LCRITERIA}}, {{TAG|ML_FF_CSLOPE}}, {{TAG|ML_FF_MHIS}}, {{TAG|ML_FF_CTIFOR}}
{{TAG|ML_LMLFF}}, {{TAG|ML_ICRITERIA}}, {{TAG|ML_CSLOPE}}, {{TAG|ML_MHIS}}, {{TAG|ML_CTIFOR}}, {{TAG|ML_CX}}


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

Latest revision as of 13:21, 8 April 2022

ML_CSIG = [real]
Default: ML_CSIG =  

Description: Parameter used in the automatic determination of threshold ML_CTIFOR for Bayesian error estimation in the machine learning force field method.


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

The standard error of the history of maximum Bayesian errors of the forces (ML_MHIS) and it's slope must be below ML_CSIG and ML_CSLOPE so that an update of the threshold for the maximum Bayesian error of forces ML_CTIFOR can take place.

Related tags and articles

ML_LMLFF, ML_ICRITERIA, ML_CSLOPE, ML_MHIS, ML_CTIFOR, ML_CX

Examples that use this tag