# Performance of Machine Learning Algorithms for Class-Imbalanced Process Fault Detection Problems

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/performance-of-machine-learning-algorithms-for-class-imbalanced-process-fault/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Tae‐Hyung Lee,Ki Bum Lee,Chang Ouk Kim |
| Citations | 65 |
| DOI | 10.1109/tsm.2016.2602226 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2512338826 |
| Type | article |
| Year | 2016 |

## Paper authors

- [Chang Ouk Kim](https://scholariq.org/researchers/chang-ouk-kim/)

## 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/)
- [Industrial Vision Systems and Defect Detection](https://scholariq.org/topics/industrial-vision-systems-and-defect-detection/)
- [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.