ML EPS LOW: Difference between revisions
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{{DISPLAYTITLE:ML_EPS_LOW}} | |||
{{TAGDEF|ML_EPS_LOW|[real]|1E-9}} (vasp.6.3.1 default was 1E-10, see comments below) | {{TAGDEF|ML_EPS_LOW|[real]|1E-9}} (vasp.6.3.1 default was 1E-10, see comments below) | ||
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[[Machine learning force field: Theory#Sparsification of local reference configurations|here]]. | [[Machine learning force field: Theory#Sparsification of local reference configurations|here]]. | ||
== Related | == Related tags and articles == | ||
{{TAG|ML_LMLFF}}, {{TAG|ML_MB}}, {{TAG|ML_EPS_REG}}, {{TAG|ML_IALGO_LINREG}} | {{TAG|ML_LMLFF}}, {{TAG|ML_MB}}, {{TAG|ML_EPS_REG}}, {{TAG|ML_IALGO_LINREG}} | ||
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[[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields | [[Category:INCAR tag]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]] | ||
Revision as of 07:23, 7 April 2022
ML_EPS_LOW = [real]
Default: ML_EPS_LOW = 1E-9 (vasp.6.3.1 default was 1E-10, see comments below)
Description: Threshold for the CUR algorithm used in the sparsification of local reference configurations within the machine learning force fields.
This value sets the threshold for the eigenvalues that contribute to the leverage scoring used in the CUR algorithm for the rank compression ("sparsification") of the local configurations (for details see appendix E of reference [1]). Small eigenvalues and those columns (local configurations) that are strongly connected with these small eigenvalues are removed by the sparsification routines. The default value is fairly well balanced, and we do not recommend to reduce the threshold to values below 1E-9. Using smaller values than 1E-9, does not improve the MLFF if Bayesian regression is used.
The description how to choose ML_EPS_LOW for accurate force fields is given here.
On the theory of the sparsification of local reference configurations see here.
Related tags and articles
ML_LMLFF, ML_MB, ML_EPS_REG, ML_IALGO_LINREG
References