Assessing the Impact of the Quality of Textual Data on Feature Representation and Machine Learning Models: Quantitative Study Using Large Language Models

This study revealed that models performed relatively well on datasets with lower error rates (<10%), but their performance declined significantly as error rates increased (≥10%). Therefore, it is crucial to evaluate the quality of a dataset before using it for machine learning tasks. For datasets with higher error rates, implementing corrective measures is essential to ensure the reliability and effectiveness of machine learning models.