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Pregled bibliografske jedinice broj: 1011968

Performance Analysis of SMOTE-Based Oversampling Techniques When Dealing with Data Imbalance


Bajer, Dražen; Zorić, Bruno; Dudjak, Mario; Martinović, Goran
Performance Analysis of SMOTE-Based Oversampling Techniques When Dealing with Data Imbalance // Proceedings of IWSSIP 2019 / Rimac-Drlje, Snježana ; Žagar, Drago ; Galić, Irena ; Martinović, Goran ; Vranješ, Denis ; Habijan, Marija (ur.).
Osijek: Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek, 2019. str. 265-271 doi:10.1109/IWSSIP.2019.8787306 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1011968 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Performance Analysis of SMOTE-Based Oversampling Techniques When Dealing with Data Imbalance

Autori
Bajer, Dražen ; Zorić, Bruno ; Dudjak, Mario ; Martinović, Goran

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of IWSSIP 2019 / Rimac-Drlje, Snježana ; Žagar, Drago ; Galić, Irena ; Martinović, Goran ; Vranješ, Denis ; Habijan, Marija - Osijek : Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek, 2019, 265-271

ISBN
978-1-7281-3253-2

Skup
2019 International Conference on Systems, Signals and Image Processing (IWSSIP)

Mjesto i datum
Osijek, Hrvatska, 05-07.06.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
classification ; data imbalance ; minority oversampling ; SMOTE

Sažetak
Building classification models on imbalanced data proves to be a challenging task despite the multitude of available classifiers. The classifier bias towards the majority class can be ameliorated through various manners and with varying degrees of success. Oversampling minority instances or undersampling majority ones are prominent amongst these due both to their simplicity and effectiveness. Probably the most popular approach to oversampling is the well-known SMOTE algorithm, based on which numerous enhancement attempts were made. This paper aims to compare the performance of these, more complex, oversampling techniques with regard to the original on a wide array of problems. Additionally, it attempts to give insight into the behaviour of different interpretations of the original algorithm apparent in the literature. In that regard, some interesting findings were made.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Projekti:
KK.01.1.1.01.0009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (EK )

Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Profili:

Avatar Url Goran Martinović (autor)

Avatar Url Dražen Bajer (autor)

Avatar Url Bruno Zorić (autor)

Avatar Url Mario Dudjak (autor)

Poveznice na cjeloviti tekst rada:

doi ieeexplore.ieee.org

Citiraj ovu publikaciju:

Bajer, Dražen; Zorić, Bruno; Dudjak, Mario; Martinović, Goran
Performance Analysis of SMOTE-Based Oversampling Techniques When Dealing with Data Imbalance // Proceedings of IWSSIP 2019 / Rimac-Drlje, Snježana ; Žagar, Drago ; Galić, Irena ; Martinović, Goran ; Vranješ, Denis ; Habijan, Marija (ur.).
Osijek: Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek, 2019. str. 265-271 doi:10.1109/IWSSIP.2019.8787306 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Bajer, D., Zorić, B., Dudjak, M. & Martinović, G. (2019) Performance Analysis of SMOTE-Based Oversampling Techniques When Dealing with Data Imbalance. U: Rimac-Drlje, S., Žagar, D., Galić, I., Martinović, G., Vranješ, D. & Habijan, M. (ur.)Proceedings of IWSSIP 2019 doi:10.1109/IWSSIP.2019.8787306.
@article{article, author = {Bajer, Dra\v{z}en and Zori\'{c}, Bruno and Dudjak, Mario and Martinovi\'{c}, Goran}, year = {2019}, pages = {265-271}, DOI = {10.1109/IWSSIP.2019.8787306}, keywords = {classification, data imbalance, minority oversampling, SMOTE}, doi = {10.1109/IWSSIP.2019.8787306}, isbn = {978-1-7281-3253-2}, title = {Performance Analysis of SMOTE-Based Oversampling Techniques When Dealing with Data Imbalance}, keyword = {classification, data imbalance, minority oversampling, SMOTE}, publisher = {Fakultet elektrotehnike, ra\v{c}unarstva i informacijskih tehnologija Osijek}, publisherplace = {Osijek, Hrvatska} }
@article{article, author = {Bajer, Dra\v{z}en and Zori\'{c}, Bruno and Dudjak, Mario and Martinovi\'{c}, Goran}, year = {2019}, pages = {265-271}, DOI = {10.1109/IWSSIP.2019.8787306}, keywords = {classification, data imbalance, minority oversampling, SMOTE}, doi = {10.1109/IWSSIP.2019.8787306}, isbn = {978-1-7281-3253-2}, title = {Performance Analysis of SMOTE-Based Oversampling Techniques When Dealing with Data Imbalance}, keyword = {classification, data imbalance, minority oversampling, SMOTE}, publisher = {Fakultet elektrotehnike, ra\v{c}unarstva i informacijskih tehnologija Osijek}, publisherplace = {Osijek, Hrvatska} }

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