Measures of Model Interpretability for Model Selection

André Carrington, Paul Fieguth, Helen Chen

Open source

DOI: 10.1007/978-3-319-99740-7_24
Published: 2018
Container: Lecture Notes in Computer Science
Publisher: Springer International Publishing
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1007/978-3-319-99740-7_24,
  title = {Measures of Model Interpretability for Model Selection},
  author = {André Carrington and Paul Fieguth and Helen Chen},
  year = {2018},
  journal = {Lecture Notes in Computer Science},
  doi = {10.1007/978-3-319-99740-7_24},
  url = {https://doi.org/10.1007/978-3-319-99740-7_24}
}

RIS

TY  - JOUR
TI  - Measures of Model Interpretability for Model Selection
AU  - André Carrington
AU  - Paul Fieguth
AU  - Helen Chen
PY  - 2018
JO  - Lecture Notes in Computer Science
DO  - 10.1007/978-3-319-99740-7_24
UR  - https://doi.org/10.1007/978-3-319-99740-7_24
ER  -

APA

Carrington, A., Fieguth, P., & Chen, H. (2018). Measures of Model Interpretability for Model Selection. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-99740-7_24

Source records

crossref · retrieved 2026-09-25T10:38:59.510Z