https://terms-en.ai-term-hub.com/zh/tags/model-evaluation/Recent content in Model Evaluation on 中文AI术语词典Hugozh-cnSat, 18 Jul 2026 11:44:45 +0000https://terms-en.ai-term-hub.com/zh/terms/overfitting/Sat, 18 Jul 2026 11:01:16 +0000https://terms-en.ai-term-hub.com/zh/terms/overfitting/<h2 id="definition">Definition</h2> <p>当模型对训练数据学习得过于完美，包括其随机噪声和异常值时，就会发生过拟合。这导致模型在训练数据上表现优异，但在新的、未见过的测试数据上表现糟糕。</p> <h3 id="summary">Summary</h3> <p>一种建模误差，机器学习算法捕捉到了噪声而非潜在信号，从而损害了泛化能力。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>高方差</li> <li>泛化能力差</li> <li>训练误差与测试误差差距大</li> <li>模型复杂度</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>诊断模型性能问题</li> <li>选择正则化强度</li> <li>确定最佳模型深度</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/underfitting-%E6%AC%A0%E6%8B%9F%E5%90%88/">underfitting (欠拟合)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/regularization-%E6%AD%A3%E5%88%99%E5%8C%96/">regularization (正则化)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/cross_validation-%E4%BA%A4%E5%8F%89%E9%AA%8C%E8%AF%81/">cross_validation (交叉验证)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/bias_variance_tradeoff-%E5%81%8F%E5%B7%AE-%E6%96%B9%E5%B7%AE%E6%9D%83%E8%A1%A1/">bias_variance_tradeoff (偏差-方差权衡)</a></li> </ul>