SVM behavior after insertion of noise.
<p>The mean AUC of the test was obtained with the insertion of noise generated by a normal distribution with 0.1 standard deviation and a 0–1.5 mean range.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , , , |
| منشور في: |
2024
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| الموضوعات: | |
| الوسوم: |
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| _version_ | 1852025874475384832 |
|---|---|
| author | Caroline L. Alves (14271413) |
| author2 | Tiago Martinelli (10402035) Loriz Francisco Sallum (19865127) Francisco Aparecido Rodrigues (19865130) Thaise G. L. de O. Toutain (19865133) Joel Augusto Moura Porto (19865136) Christiane Thielemann (14271419) Patrícia Maria de Carvalho Aguiar (19865139) Michael Moeckel (19865142) |
| author2_role | author author author author author author author author |
| author_facet | Caroline L. Alves (14271413) Tiago Martinelli (10402035) Loriz Francisco Sallum (19865127) Francisco Aparecido Rodrigues (19865130) Thaise G. L. de O. Toutain (19865133) Joel Augusto Moura Porto (19865136) Christiane Thielemann (14271419) Patrícia Maria de Carvalho Aguiar (19865139) Michael Moeckel (19865142) |
| author_role | author |
| dc.creator.none.fl_str_mv | Caroline L. Alves (14271413) Tiago Martinelli (10402035) Loriz Francisco Sallum (19865127) Francisco Aparecido Rodrigues (19865130) Thaise G. L. de O. Toutain (19865133) Joel Augusto Moura Porto (19865136) Christiane Thielemann (14271419) Patrícia Maria de Carvalho Aguiar (19865139) Michael Moeckel (19865142) |
| dc.date.none.fl_str_mv | 2024-10-17T17:35:08Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0305630.g008 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/SVM_behavior_after_insertion_of_noise_/27251097 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Cell Biology Neuroscience Biotechnology Science Policy Mental Health Biological Sciences not elsewhere classified totaling 120 subjects targeted intervention difficult surpassing existing benchmarks observed connectivity patterns brain network integration autism spectrum disorder achieve superior accuracy brain regions critical leveraging multiclass classification asd show disruptions ml classification rests multiclass classification regions involved typically developed three groups segregation among promising avenue overlapping symptoms impulse control findings pave established practices enhanced diagnostics cognitive functions clinical symptoms accurate diagnosis |
| dc.title.none.fl_str_mv | SVM behavior after insertion of noise. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>The mean AUC of the test was obtained with the insertion of noise generated by a normal distribution with 0.1 standard deviation and a 0–1.5 mean range.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_cb33ddd63eb73a5ac5b9c4fc2d2c2f7d |
| identifier_str_mv | 10.1371/journal.pone.0305630.g008 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/27251097 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | SVM behavior after insertion of noise.Caroline L. Alves (14271413)Tiago Martinelli (10402035)Loriz Francisco Sallum (19865127)Francisco Aparecido Rodrigues (19865130)Thaise G. L. de O. Toutain (19865133)Joel Augusto Moura Porto (19865136)Christiane Thielemann (14271419)Patrícia Maria de Carvalho Aguiar (19865139)Michael Moeckel (19865142)MedicineCell BiologyNeuroscienceBiotechnologyScience PolicyMental HealthBiological Sciences not elsewhere classifiedtotaling 120 subjectstargeted intervention difficultsurpassing existing benchmarksobserved connectivity patternsbrain network integrationautism spectrum disorderachieve superior accuracybrain regions criticalleveraging multiclass classificationasd show disruptionsml classification restsmulticlass classificationregions involvedtypically developedthree groupssegregation amongpromising avenueoverlapping symptomsimpulse controlfindings paveestablished practicesenhanced diagnosticscognitive functionsclinical symptomsaccurate diagnosis<p>The mean AUC of the test was obtained with the insertion of noise generated by a normal distribution with 0.1 standard deviation and a 0–1.5 mean range.</p>2024-10-17T17:35:08ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0305630.g008https://figshare.com/articles/figure/SVM_behavior_after_insertion_of_noise_/27251097CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/272510972024-10-17T17:35:08Z |
| spellingShingle | SVM behavior after insertion of noise. Caroline L. Alves (14271413) Medicine Cell Biology Neuroscience Biotechnology Science Policy Mental Health Biological Sciences not elsewhere classified totaling 120 subjects targeted intervention difficult surpassing existing benchmarks observed connectivity patterns brain network integration autism spectrum disorder achieve superior accuracy brain regions critical leveraging multiclass classification asd show disruptions ml classification rests multiclass classification regions involved typically developed three groups segregation among promising avenue overlapping symptoms impulse control findings pave established practices enhanced diagnostics cognitive functions clinical symptoms accurate diagnosis |
| status_str | publishedVersion |
| title | SVM behavior after insertion of noise. |
| title_full | SVM behavior after insertion of noise. |
| title_fullStr | SVM behavior after insertion of noise. |
| title_full_unstemmed | SVM behavior after insertion of noise. |
| title_short | SVM behavior after insertion of noise. |
| title_sort | SVM behavior after insertion of noise. |
| topic | Medicine Cell Biology Neuroscience Biotechnology Science Policy Mental Health Biological Sciences not elsewhere classified totaling 120 subjects targeted intervention difficult surpassing existing benchmarks observed connectivity patterns brain network integration autism spectrum disorder achieve superior accuracy brain regions critical leveraging multiclass classification asd show disruptions ml classification rests multiclass classification regions involved typically developed three groups segregation among promising avenue overlapping symptoms impulse control findings pave established practices enhanced diagnostics cognitive functions clinical symptoms accurate diagnosis |