ML CX: Difference between revisions
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Description: The parameter determines how the threshold ({{TAG|ML_CTIFOR}}) is updated within the machine learning force field methods. | Description: The parameter determines how the threshold ({{TAG|ML_CTIFOR}}) is updated within the machine learning force field methods. | ||
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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]]. | ||
If {{TAG|ML_ICRITERIA}}>0, | If {{TAG|ML_ICRITERIA}}>0, | ||
Revision as of 10:15, 2 November 2021
ML_CX = [integer]
Default: ML_CX = 0.0
Description: The parameter determines how the threshold (ML_CTIFOR) is updated within the machine learning force field methods.
The usage of this tag in combination with the learning algorithms is described here: here.
If ML_ICRITERIA>0, ML_CTIFOR is set to the average of the Bayesian errors of the forces stored in history (see ML_ICRITERIA). The number of entries in the history are controlled by ML_MHIS.
This implies that for ML_CX=0, the old value stored in ML_CTIFOR is simply overwritten by the current average Bayesian error.
Related Tags and Sections
ML_LMLFF, ML_ICRITERIA, ML_CTIFOR, ML_MHIS, ML_CSIG, ML_CSLOPE