Performance measures for ML models of synthesized dataset by TVAE.

<p>Performance measures for ML models of synthesized dataset by TVAE.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Kazi Arman Ahmed (21567972) (author)
مؤلفون آخرون: Israt Humaira (21567975) (author), Ashiqur Rahman Khan (21567978) (author), Md Shamim Hasan (20721344) (author), Mukitul Islam (21567981) (author), Anik Roy (11688974) (author), Mehrab Karim (21567984) (author), Mezbah Uddin (21567987) (author), Ashique Mohammad (21567990) (author), Md Doulotuzzaman Xames (21567993) (author)
منشور في: 2025
الموضوعات:
الوسوم: إضافة وسم
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_version_ 1852019214404026368
author Kazi Arman Ahmed (21567972)
author2 Israt Humaira (21567975)
Ashiqur Rahman Khan (21567978)
Md Shamim Hasan (20721344)
Mukitul Islam (21567981)
Anik Roy (11688974)
Mehrab Karim (21567984)
Mezbah Uddin (21567987)
Ashique Mohammad (21567990)
Md Doulotuzzaman Xames (21567993)
author2_role author
author
author
author
author
author
author
author
author
author_facet Kazi Arman Ahmed (21567972)
Israt Humaira (21567975)
Ashiqur Rahman Khan (21567978)
Md Shamim Hasan (20721344)
Mukitul Islam (21567981)
Anik Roy (11688974)
Mehrab Karim (21567984)
Mezbah Uddin (21567987)
Ashique Mohammad (21567990)
Md Doulotuzzaman Xames (21567993)
author_role author
dc.creator.none.fl_str_mv Kazi Arman Ahmed (21567972)
Israt Humaira (21567975)
Ashiqur Rahman Khan (21567978)
Md Shamim Hasan (20721344)
Mukitul Islam (21567981)
Anik Roy (11688974)
Mehrab Karim (21567984)
Mezbah Uddin (21567987)
Ashique Mohammad (21567990)
Md Doulotuzzaman Xames (21567993)
dc.date.none.fl_str_mv 2025-06-18T17:45:39Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0326221.t006
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Performance_measures_for_ML_models_of_synthesized_dataset_by_TVAE_/29359260
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biotechnology
Cancer
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
predicting breast cancer
necessitating improved approaches
improve prediction performance
improve prediction accuracy
breast cancer diagnosis
traditional ml models
models using original
based ensemble strategies
ensemble models
ml models
two stages
third phases
synthetic datasets
study demonstrated
stratified k
rising incidence
original dataset
mortality rates
model ensembles
including knn
gaussian copula
fold cross
first stage
findings underscore
deep learning
comparative analysis
based multi
aiding decision
dc.title.none.fl_str_mv Performance measures for ML models of synthesized dataset by TVAE.
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <p>Performance measures for ML models of synthesized dataset by TVAE.</p>
eu_rights_str_mv openAccess
id Manara_aefcf94b7341cf5cef7e018dad5f0ca2
identifier_str_mv 10.1371/journal.pone.0326221.t006
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/29359260
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Performance measures for ML models of synthesized dataset by TVAE.Kazi Arman Ahmed (21567972)Israt Humaira (21567975)Ashiqur Rahman Khan (21567978)Md Shamim Hasan (20721344)Mukitul Islam (21567981)Anik Roy (11688974)Mehrab Karim (21567984)Mezbah Uddin (21567987)Ashique Mohammad (21567990)Md Doulotuzzaman Xames (21567993)BiotechnologyCancerBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedpredicting breast cancernecessitating improved approachesimprove prediction performanceimprove prediction accuracybreast cancer diagnosistraditional ml modelsmodels using originalbased ensemble strategiesensemble modelsml modelstwo stagesthird phasessynthetic datasetsstudy demonstratedstratified krising incidenceoriginal datasetmortality ratesmodel ensemblesincluding knngaussian copulafold crossfirst stagefindings underscoredeep learningcomparative analysisbased multiaiding decision<p>Performance measures for ML models of synthesized dataset by TVAE.</p>2025-06-18T17:45:39ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0326221.t006https://figshare.com/articles/dataset/Performance_measures_for_ML_models_of_synthesized_dataset_by_TVAE_/29359260CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/293592602025-06-18T17:45:39Z
spellingShingle Performance measures for ML models of synthesized dataset by TVAE.
Kazi Arman Ahmed (21567972)
Biotechnology
Cancer
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
predicting breast cancer
necessitating improved approaches
improve prediction performance
improve prediction accuracy
breast cancer diagnosis
traditional ml models
models using original
based ensemble strategies
ensemble models
ml models
two stages
third phases
synthetic datasets
study demonstrated
stratified k
rising incidence
original dataset
mortality rates
model ensembles
including knn
gaussian copula
fold cross
first stage
findings underscore
deep learning
comparative analysis
based multi
aiding decision
status_str publishedVersion
title Performance measures for ML models of synthesized dataset by TVAE.
title_full Performance measures for ML models of synthesized dataset by TVAE.
title_fullStr Performance measures for ML models of synthesized dataset by TVAE.
title_full_unstemmed Performance measures for ML models of synthesized dataset by TVAE.
title_short Performance measures for ML models of synthesized dataset by TVAE.
title_sort Performance measures for ML models of synthesized dataset by TVAE.
topic Biotechnology
Cancer
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
predicting breast cancer
necessitating improved approaches
improve prediction performance
improve prediction accuracy
breast cancer diagnosis
traditional ml models
models using original
based ensemble strategies
ensemble models
ml models
two stages
third phases
synthetic datasets
study demonstrated
stratified k
rising incidence
original dataset
mortality rates
model ensembles
including knn
gaussian copula
fold cross
first stage
findings underscore
deep learning
comparative analysis
based multi
aiding decision