FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2849202363> ?p ?o ?g. }

• W2849202363 abstract "Recently, Saeb et al (2017) showed that, in diagnostic machine learning applications, having data of each randomly assigned to both training and test sets (record-wise data split) can lead to massive underestimation of the cross-validation prediction error, due to the presence of subject identity confounding caused by the classifier's ability to identify subjects, instead of recognizing disease. To solve this problem, the authors recommended the random assignment of the data of each to either the training or the test set (subject-wise data split). The adoption of subject-wise split has been criticized in Little et al (2017), on the basis that it can violate assumptions required by cross-validation to consistently estimate generalization error. In particular, adopting subject-wise splitting in heterogeneous data-sets might lead to model under-fitting and larger classification errors. Hence, Little et al argue that perhaps the overestimation of prediction errors with subject-wise cross-validation, rather than underestimation with record-wise cross-validation, is the reason for the discrepancies between prediction error estimates generated by the two splitting strategies. In order to shed light on this controversy, we focus on simpler classification performance metrics and develop permutation tests that can detect identity confounding. By focusing on permutation tests, we are able to evaluate the merits of record-wise and subject-wise data splits under more general statistical dependencies and distributional structures of the data, including situations where cross-validation breaks down. We illustrate the application of our tests using synthetic and real data from a Parkinson's disease study." @default.
• W2849202363 created "2018-07-19" @default.
• W2849202363 creator A5002032395 @default.
• W2849202363 creator A5029959684 @default.
• W2849202363 creator A5033638597 @default.
• W2849202363 creator A5038454932 @default.
• W2849202363 creator A5043737761 @default.
• W2849202363 creator A5054208950 @default.
• W2849202363 creator A5069348884 @default.
• W2849202363 creator A5074643952 @default.
• W2849202363 creator A5091295638 @default.
• W2849202363 date "2017-12-08" @default.
• W2849202363 modified "2023-09-27" @default.
• W2849202363 title "Learning Disease vs Participant Signatures: a permutation test approach to detect identity confounding in machine learning diagnostic applications" @default.
• W2849202363 cites W1990534247 @default.
• W2849202363 cites W2029694543 @default.
• W2849202363 cites W2075987325 @default.
• W2849202363 cites W2095134828 @default.
• W2849202363 cites W2170517798 @default.
• W2849202363 cites W2296350496 @default.
• W2849202363 cites W2329665940 @default.
• W2849202363 cites W2727885084 @default.
• W2849202363 cites W2911964244 @default.
• W2849202363 hasPublicationYear "2017" @default.
• W2849202363 type Work @default.
• W2849202363 sameAs 2849202363 @default.
• W2849202363 citedByCount "1" @default.
• W2849202363 countsByYear W28492023632018 @default.
• W2849202363 crossrefType "posted-content" @default.
• W2849202363 hasAuthorship W2849202363A5002032395 @default.
• W2849202363 hasAuthorship W2849202363A5029959684 @default.
• W2849202363 hasAuthorship W2849202363A5033638597 @default.
• W2849202363 hasAuthorship W2849202363A5038454932 @default.
• W2849202363 hasAuthorship W2849202363A5043737761 @default.
• W2849202363 hasAuthorship W2849202363A5054208950 @default.
• W2849202363 hasAuthorship W2849202363A5069348884 @default.
• W2849202363 hasAuthorship W2849202363A5074643952 @default.
• W2849202363 hasAuthorship W2849202363A5091295638 @default.
• W2849202363 hasConcept C105795698 @default.
• W2849202363 hasConcept C11413529 @default.
• W2849202363 hasConcept C119857082 @default.
• W2849202363 hasConcept C121332964 @default.
• W2849202363 hasConcept C150921843 @default.
• W2849202363 hasConcept C154945302 @default.
• W2849202363 hasConcept C16910744 @default.
• W2849202363 hasConcept C169903167 @default.
• W2849202363 hasConcept C199360897 @default.
• W2849202363 hasConcept C21308566 @default.
• W2849202363 hasConcept C24890656 @default.
• W2849202363 hasConcept C27181475 @default.
• W2849202363 hasConcept C2778355321 @default.
• W2849202363 hasConcept C33923547 @default.
• W2849202363 hasConcept C41008148 @default.
• W2849202363 hasConcept C51632099 @default.
• W2849202363 hasConcept C77350462 @default.
• W2849202363 hasConcept C95623464 @default.
• W2849202363 hasConceptScore W2849202363C105795698 @default.
• W2849202363 hasConceptScore W2849202363C11413529 @default.
• W2849202363 hasConceptScore W2849202363C119857082 @default.
• W2849202363 hasConceptScore W2849202363C121332964 @default.
• W2849202363 hasConceptScore W2849202363C150921843 @default.
• W2849202363 hasConceptScore W2849202363C154945302 @default.
• W2849202363 hasConceptScore W2849202363C16910744 @default.
• W2849202363 hasConceptScore W2849202363C169903167 @default.
• W2849202363 hasConceptScore W2849202363C199360897 @default.
• W2849202363 hasConceptScore W2849202363C21308566 @default.
• W2849202363 hasConceptScore W2849202363C24890656 @default.
• W2849202363 hasConceptScore W2849202363C27181475 @default.
• W2849202363 hasConceptScore W2849202363C2778355321 @default.
• W2849202363 hasConceptScore W2849202363C33923547 @default.
• W2849202363 hasConceptScore W2849202363C41008148 @default.
• W2849202363 hasConceptScore W2849202363C51632099 @default.
• W2849202363 hasConceptScore W2849202363C77350462 @default.
• W2849202363 hasConceptScore W2849202363C95623464 @default.
• W2849202363 hasLocation W28492023631 @default.
• W2849202363 hasOpenAccess W2849202363 @default.
• W2849202363 hasPrimaryLocation W28492023631 @default.
• W2849202363 hasRelatedWork W15509920 @default.
• W2849202363 hasRelatedWork W2037758579 @default.
• W2849202363 hasRelatedWork W2055672407 @default.
• W2849202363 hasRelatedWork W2072717937 @default.
• W2849202363 hasRelatedWork W2118930608 @default.
• W2849202363 hasRelatedWork W2568254335 @default.
• W2849202363 hasRelatedWork W2618438111 @default.
• W2849202363 hasRelatedWork W2737604683 @default.
• W2849202363 hasRelatedWork W2804082618 @default.
• W2849202363 hasRelatedWork W2912757738 @default.
• W2849202363 hasRelatedWork W2915013339 @default.
• W2849202363 hasRelatedWork W2972590742 @default.
• W2849202363 hasRelatedWork W3015646389 @default.
• W2849202363 hasRelatedWork W3096516513 @default.
• W2849202363 hasRelatedWork W3129912876 @default.
• W2849202363 hasRelatedWork W3177397812 @default.
• W2849202363 hasRelatedWork W3198616475 @default.
• W2849202363 hasRelatedWork W3213231108 @default.
• W2849202363 hasRelatedWork W940094962 @default.
• W2849202363 hasRelatedWork W1764975672 @default.
• W2849202363 isParatext "false" @default.
• W2849202363 isRetracted "false" @default.
• W2849202363 magId "2849202363" @default.

• next