Handling Label Errors in Text Classification Datasets
Recent studies have found that even highly curated machine learning benchmark datasets contain label errors, which can significantly impact model performance. The open-source cleanlab library provides a standard framework for identifying and addressing these issues in real-world data. In this hands-on blog, the authors demonstrate how to use cleanlab to find label problems in the IMDb movie review text classification dataset and improve models without changing them. They also provide code examples for implementing the workflow on other datasets.
Company
Cleanlab
Date published
May 10, 2022
Author(s)
Wei Jing Lok, Jonas Mueller, Hui Wen Goh
Word count
3490
Language
English
Hacker News points
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