ML NMDINT: Difference between revisions

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{{DISPLAYTITLE:ML_NMDINT}}
{{DISPLAYTITLE:ML_NMDINT}}
{{TAGDEF|ML_NMDINT|[integer]|10}}
{{TAGDEF|ML_NMDINT|[integer]}}
{{DEF|ML_NMDINT|1|for {{TAG|ML_MODE}} {{=}} SELECT|10|else}}


Description: Tag to control the minimum interval to get training samples in the machine learning force field method.
Description: Tag to control the minimum interval to get training samples 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#Sampling of training data and local reference configurations|here]]
The usage of this tag in combination with the learning algorithms is described here: [[Machine_learning_force_field:_Theory#Sampling_of_training_data_and_local_reference_configurations|here]]


This tag defines a lower threshold for taking new configurations from the MD, so that as long as the upper threshold for the Bayesian error (e.g. {{TAG|ML_CDOUB}} times {{TAG|ML_CTIFOR}}) is not exceeded,  at least {{TAG|ML_NMDINT}} MD steps are preformed using the MLFF (i.e. no first principles calculation is performed). This avoids that many nearly identical structures are added.
This tag defines a lower threshold for taking new configurations from the MD, so that as long as the upper threshold for the Bayesian error (e.g. {{TAG|ML_CDOUB}} times {{TAG|ML_CTIFOR}}) is not exceeded,  at least {{TAG|ML_NMDINT}} MD steps are preformed using the MLFF (i.e. no first principles calculation is performed). This avoids that many nearly identical structures are added.
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[[Category:INCAR tag]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]]
[[Category:INCAR tag]][[Category:Machine-learned force fields]]

Latest revision as of 09:47, 8 November 2023

ML_NMDINT = [integer] 

Default: ML_NMDINT = 1 for ML_MODE = SELECT
= 10 else

Description: Tag to control the minimum interval to get training samples in the machine learning force field method.


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

This tag defines a lower threshold for taking new configurations from the MD, so that as long as the upper threshold for the Bayesian error (e.g. ML_CDOUB times ML_CTIFOR) is not exceeded, at least ML_NMDINT MD steps are preformed using the MLFF (i.e. no first principles calculation is performed). This avoids that many nearly identical structures are added.

Related tags and articles

ML_LMLFF, ML_MCONF_NEW, ML_CDOUB, ML_CTIFOR, ML_MHIS

Examples that use this tag