ML ICRITERIA: Difference between revisions

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

Revision as of 13:24, 8 April 2022

ML_ICRITERIA = [integer]
Default: ML_ICRITERIA = 1 

Description: Decides whether (ML_ICRITERIA>0) or how the Bayesian error threshold (ML_CTIFOR) is updated within the machine learning force field method. ML_CTIFOR determines whether a first principles calculations is performed.


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

The following options are possible for ML_ICRITERIA:

  • ML_ICRITERIA = 0: No update of the threshold ML_CTIFOR is done.
  • ML_ICRITERIA = 1: Update of criteria using average of the Bayesian errors of the forces from history (see description of method here).
  • ML_ICRITERIA = 2: Update of criteria using gliding average of Bayesian errors (probably more robust but not well tested).

Related tags and articles

ML_LMLFF, ML_CTIFOR, ML_CSLOPE, ML_CSIG, ML_MHIS, ML_XMIX

Examples that use this tag