LoRAS: an oversampling approach for imbalanced datasets

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1573-0565

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: LoRAS: an oversampling approach for imbalanced datasets ; day:12 ; month:11 ; year:2020 ; pages:1-23
Machine learning ; (12.11.2020), 1-23

Creator: Bej, Saptarshi
Davtyan, Narek
Wolfien, Markus
Nassar, Mariam
Wolkenhauer, Olaf

Contributor: SpringerLink (Online service)

DOI: 10.1007/s10994-020-05913-4

URN: urn:nbn:de:101:1-2020122320221566674012

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:28 AM CEST

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Bej, Saptarshi
Davtyan, Narek
Wolfien, Markus
Nassar, Mariam
Wolkenhauer, Olaf
SpringerLink (Online service)

Other Objects (12)

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Eigenwerbung LoRa

Bootstrapping binary GEV regressions for imbalanced datasets

Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers

Resampling imbalanced data for network intrusion detection datasets

Correction to: Bootstrapping binary GEV regressions for imbalanced datasets

Handling imbalanced medical datasets: review of a decade of research

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

Personalakten

Lora

On-the-fly image-level oversampling for imbalanced datasets of manufacturing defects

Underground LoRa Sensor Node for Bushfire Monitoring

A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE

Personenakten

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Objekte

Eigenwerbung LoRa

Bootstrapping binary GEV regressions for imbalanced datasets

Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers

Resampling imbalanced data for network intrusion detection datasets

Correction to: Bootstrapping binary GEV regressions for imbalanced datasets

Handling imbalanced medical datasets: review of a decade of research

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

Personalakten

Lora

On-the-fly image-level oversampling for imbalanced datasets of manufacturing defects

Underground LoRa Sensor Node for Bushfire Monitoring

A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE

Personenakten

Loras, Ferenc

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LoRAS: an oversampling approach for imbalanced datasets

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Other Objects (12)

Eigenwerbung LoRa

Bootstrapping binary GEV regressions for imbalanced datasets

Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers

Resampling imbalanced data for network intrusion detection datasets

Correction to: Bootstrapping binary GEV regressions for imbalanced datasets

Handling imbalanced medical datasets: review of a decade of research

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

Lora

On-the-fly image-level oversampling for imbalanced datasets of manufacturing defects

Underground LoRa Sensor Node for Bushfire Monitoring

A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE

Loras, Ferenc

Eigenwerbung LoRa

Bootstrapping binary GEV regressions for imbalanced datasets

Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers

Resampling imbalanced data for network intrusion detection datasets

Correction to: Bootstrapping binary GEV regressions for imbalanced datasets

Handling imbalanced medical datasets: review of a decade of research

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

Lora

On-the-fly image-level oversampling for imbalanced datasets of manufacturing defects

Underground LoRa Sensor Node for Bushfire Monitoring

A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE

Loras, Ferenc

Eigenwerbung LoRa

Bootstrapping binary GEV regressions for imbalanced datasets

Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers

Resampling imbalanced data for network intrusion detection datasets

Correction to: Bootstrapping binary GEV regressions for imbalanced datasets

Handling imbalanced medical datasets: review of a decade of research

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

Lora

On-the-fly image-level oversampling for imbalanced datasets of manufacturing defects

Underground LoRa Sensor Node for Bushfire Monitoring

A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE

Loras, Ferenc

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