ML ICRITERIA: Difference between revisions
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* {{TAG|ML_ICRITERIA}} = 1: Update of criteria using average of the Bayesian errors of the forces from history (see description of method below). | * {{TAG|ML_ICRITERIA}} = 1: Update of criteria using average of the Bayesian errors of the forces from history (see description of method below). | ||
* {{TAG|ML_ICRITERIA}} = 2: Update of criteria using gliding average of Bayesian errors (probably more robust but '''not well tested'''). | * {{TAG|ML_ICRITERIA}} = 2: Update of criteria using gliding average of Bayesian errors (probably more robust but '''not well tested'''). | ||
== Related Tags and Sections == | == Related Tags and Sections == | ||
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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]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] | [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] | ||
Revision as of 17:25, 21 October 2021
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 below).
- ML_ICRITERIA = 2: Update of criteria using gliding average of Bayesian errors (probably more robust but not well tested).
Related Tags and Sections
ML_LMLFF, ML_CTIFOR, ML_CSLOPE, ML_CSIG, ML_MHIS, ML_XMIX