https://terms-en.ai-term-hub.com/en/tags/machine-learning-basics/Recent content in Machine Learning Basics on English AI Terms DictionaryHugoen-usSat, 18 Jul 2026 11:44:44 +0000https://terms-en.ai-term-hub.com/en/terms/label_noise/Sat, 18 Jul 2026 10:04:10 +0000https://terms-en.ai-term-hub.com/en/terms/label_noise/<h2 id="definition">Definition</h2> <p>Label noise refers to discrepancies between the true class labels of data instances and the labels provided in the training dataset. This can arise from human annotation errors, ambiguous data points, or systematic labeling biases. Noise can be symmetric (random mislabeling) or asymmetric (specific classes mislabeled as others). It degrades model performance and generalization, necessitating robust learning techniques such as noise-tolerant loss functions, data cleaning, or ensemble methods to mitigate its adverse effects during training.</p>