# A Comparison of Undersampling, Oversampling, and SMOTE Methods for Dealing with Imbalanced Classification in Educational Data Mining

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-comparison-of-undersampling-oversampling-and-smote-methods-for-dealing-with/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Tarid Wongvorachan,Surina He,Okan Bulut |
| Citations | 354 |
| DOI | 10.3390/info14010054 |
| Fields | Business, Management and Accounting,Computer Science,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2078-2489/14/1/54/pdf?version=1673866802 |
| OpenAlex ID | https://openalex.org/W4316469706 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Okan Bulut](https://scholariq.org/researchers/okan-bulut/)

## Paper primary topic

- [Imbalanced Data Classification Techniques](https://scholariq.org/topics/imbalanced-data-classification-techniques/)

## Paper topics

- [Imbalanced Data Classification Techniques](https://scholariq.org/topics/imbalanced-data-classification-techniques/)
- [Financial Distress and Bankruptcy Prediction](https://scholariq.org/topics/financial-distress-and-bankruptcy-prediction/)
- [Electricity Theft Detection Techniques](https://scholariq.org/topics/electricity-theft-detection-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.