ML ICRITERIA: Difference between revisions
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Description: Decides whether ({{TAG|ML_ICRITERIA}}>0) or how the Bayesian error threshold ({{TAG|ML_CTIFOR}}) is updated within the machine learning force field method. {{TAG|ML_CTIFOR}} determines whether a first principles calculations is performed. | Description: Decides whether ({{TAG|ML_ICRITERIA}}>0) or how the Bayesian error threshold ({{TAG|ML_CTIFOR}}) is updated within the machine learning force field method. {{TAG|ML_CTIFOR}} determines whether a first principles calculations is performed. | ||
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The usage of this tag in combination with the learning algorithms is described here: [[Machine learning force field calculations: | 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]]. | ||
The following options are possible for {{TAG|ML_ICRITERIA}}: | The following options are possible for {{TAG|ML_ICRITERIA}}: | ||
Revision as of 10:09, 2 November 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