Validation of experimental charge-density refinement strategies: when do we overfit?
A cross-validation method is supplied to judge between various strategies in multipole refinement procedures. Its application enables straightforward detection of whether the refinement of additional parameters leads to an improvement in the model or an overfitting of the given data. For all tested...
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doaj-5deb95765a134fc98e33bc6e4a7a40ec2020-11-24T23:41:40ZengInternational Union of CrystallographyIUCrJ2052-25252017-07-014442043010.1107/S2052252517005103lc5072Validation of experimental charge-density refinement strategies: when do we overfit?Lennard Krause0Benedikt Niepötter1Christian J. Schürmann2Dietmar Stalke3Regine Herbst-Irmer4Institut für Anorganische Chemie, Universität Göttingen, Tammannstraße 4, Göttingen 37077, GermanyInstitut für Anorganische Chemie, Universität Göttingen, Tammannstraße 4, Göttingen 37077, GermanyInstitut für Anorganische Chemie, Universität Göttingen, Tammannstraße 4, Göttingen 37077, GermanyInstitut für Anorganische Chemie, Universität Göttingen, Tammannstraße 4, Göttingen 37077, GermanyInstitut für Anorganische Chemie, Universität Göttingen, Tammannstraße 4, Göttingen 37077, GermanyA cross-validation method is supplied to judge between various strategies in multipole refinement procedures. Its application enables straightforward detection of whether the refinement of additional parameters leads to an improvement in the model or an overfitting of the given data. For all tested data sets it was possible to prove that the multipole parameters of atoms in comparable chemical environments should be constrained to be identical. In an automated approach, this method additionally delivers parameter distributions of k different refinements. These distributions can be used for further error diagnostics, e.g. to detect erroneously defined parameters or incorrectly determined reflections. Visualization tools show the variation in the parameters. These different refinements also provide rough estimates for the standard deviation of topological parameters.http://scripts.iucr.org/cgi-bin/paper?S2052252517005103charge densitycross-validationerror detectionRfreerefinement strategies |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lennard Krause Benedikt Niepötter Christian J. Schürmann Dietmar Stalke Regine Herbst-Irmer |
spellingShingle |
Lennard Krause Benedikt Niepötter Christian J. Schürmann Dietmar Stalke Regine Herbst-Irmer Validation of experimental charge-density refinement strategies: when do we overfit? IUCrJ charge density cross-validation error detection Rfree refinement strategies |
author_facet |
Lennard Krause Benedikt Niepötter Christian J. Schürmann Dietmar Stalke Regine Herbst-Irmer |
author_sort |
Lennard Krause |
title |
Validation of experimental charge-density refinement strategies: when do we overfit? |
title_short |
Validation of experimental charge-density refinement strategies: when do we overfit? |
title_full |
Validation of experimental charge-density refinement strategies: when do we overfit? |
title_fullStr |
Validation of experimental charge-density refinement strategies: when do we overfit? |
title_full_unstemmed |
Validation of experimental charge-density refinement strategies: when do we overfit? |
title_sort |
validation of experimental charge-density refinement strategies: when do we overfit? |
publisher |
International Union of Crystallography |
series |
IUCrJ |
issn |
2052-2525 |
publishDate |
2017-07-01 |
description |
A cross-validation method is supplied to judge between various strategies in multipole refinement procedures. Its application enables straightforward detection of whether the refinement of additional parameters leads to an improvement in the model or an overfitting of the given data. For all tested data sets it was possible to prove that the multipole parameters of atoms in comparable chemical environments should be constrained to be identical. In an automated approach, this method additionally delivers parameter distributions of k different refinements. These distributions can be used for further error diagnostics, e.g. to detect erroneously defined parameters or incorrectly determined reflections. Visualization tools show the variation in the parameters. These different refinements also provide rough estimates for the standard deviation of topological parameters. |
topic |
charge density cross-validation error detection Rfree refinement strategies |
url |
http://scripts.iucr.org/cgi-bin/paper?S2052252517005103 |
work_keys_str_mv |
AT lennardkrause validationofexperimentalchargedensityrefinementstrategieswhendoweoverfit AT benediktniepotter validationofexperimentalchargedensityrefinementstrategieswhendoweoverfit AT christianjschurmann validationofexperimentalchargedensityrefinementstrategieswhendoweoverfit AT dietmarstalke validationofexperimentalchargedensityrefinementstrategieswhendoweoverfit AT regineherbstirmer validationofexperimentalchargedensityrefinementstrategieswhendoweoverfit |
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1725506087496450048 |