Algorithm on 中文AI术语词典https://terms-en.ai-term-hub.com/zh/tags/algorithm/Recent content in Algorithm on 中文AI术语词典Hugozh-cnSat, 18 Jul 2026 11:44:45 +0000乘法权重更新法https://terms-en.ai-term-hub.com/zh/terms/multiplicative_weight_update_method/Sat, 18 Jul 2026 11:27:47 +0000https://terms-en.ai-term-hub.com/zh/terms/multiplicative_weight_update_method/<h2 id="definition">Definition</h2> <p>乘法权重更新法是一种基础的在线学习算法，用于在不确定环境中做出决策。它为不同的策略或专家维护一组权重，并根据其表现动态调整这些权重，从而优化长期决策效果。</p> <h3 id="summary">Summary</h3> <p>一种迭代算法，根据性能反馈以乘法方式更新权重，以最小化遗憾值。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>在线学习</li> <li>加权多数算法</li> <li>遗憾最小化</li> <li>指数加权</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>投资组合优化</li> <li>专家建议聚合</li> <li>对抗性老虎机问题</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/gradient_descent-%E6%A2%AF%E5%BA%A6%E4%B8%8B%E9%99%8D/">gradient_descent (梯度下降)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/online_learning-%E5%9C%A8%E7%BA%BF%E5%AD%A6%E4%B9%A0/">online_learning (在线学习)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/regret_bound-%E9%81%97%E6%86%BE%E7%95%8C/">regret_bound (遗憾界)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/boosting-%E6%8F%90%E5%8D%87%E7%AE%97%E6%B3%95/">boosting (提升算法)</a></li> </ul>基于实例的学习https://terms-en.ai-term-hub.com/zh/terms/instance_based_learning/Sat, 18 Jul 2026 11:22:25 +0000https://terms-en.ai-term-hub.com/zh/terms/instance_based_learning/<h2 id="definition">Definition</h2> <p>也称为基于记忆的学习，该技术不在训练期间构建泛化模型。相反，它存储整个训练数据集。当需要预测时，它会找到最相似的。</p> <h3 id="summary">Summary</h3> <p>一种惰性学习方法，通过将新输入与存储的训练实例进行比较来进行预测。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>惰性学习</li> <li>相似度度量</li> <li>K近邻 (K-Nearest Neighbors)</li> <li>基于记忆</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>推荐系统</li> <li>模式识别</li> <li>中小型数据集</li> </ul> <h2 id="code-example">Code Example</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#f92672">from</span> sklearn.neighbors <span style="color:#f92672">import</span> KNeighborsClassifier </span></span><span style="display:flex;"><span>knn <span style="color:#f92672">=</span> KNeighborsClassifier(n_neighbors<span style="color:#f92672">=</span><span style="color:#ae81ff">3</span>) </span></span><span style="display:flex;"><span>knn<span style="color:#f92672">.</span>fit(X_train, y_train) </span></span></code></pre></div><h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/knn-k-nearest-neighbors/">KNN (K-Nearest Neighbors)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/%E7%9B%B8%E4%BC%BC%E5%BA%A6%E6%90%9C%E7%B4%A2-similarity-search/">相似度搜索 (Similarity search)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/%E6%83%B0%E6%80%A7%E5%AD%A6%E4%B9%A0-lazy-learning/">惰性学习 (Lazy learning)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/%E6%A0%B8%E6%96%B9%E6%B3%95-kernel-methods/">核方法 (Kernel methods)</a></li> </ul>协同训练https://terms-en.ai-term-hub.com/zh/terms/co_training/Sat, 18 Jul 2026 11:10:07 +0000https://terms-en.ai-term-hub.com/zh/terms/co_training/<h2 id="definition">Definition</h2> <p>该方法利用同一数据点的多个不同特征集（视图）。最初，在每个视图的小规模标注数据集上训练两个分类器。随后，它们对未标记数据进行预测，并仅选择高置信度的标签来辅助对方模型的训练。</p> <h3 id="summary">Summary</h3> <p>协同训练是一种半监督学习算法，利用数据的两个视图训练独立的分类器，这些分类器迭代地为彼此标记未标记数据。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>半监督学习</li> <li>多视图</li> <li>迭代标记</li> <li>高置信度选择</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>具有多特征的文本分类</li> <li>网页分类</li> <li>有限标签下的数据增强</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/semi-supervised-learning-%E5%8D%8A%E7%9B%91%E7%9D%A3%E5%AD%A6%E4%B9%A0/">Semi-Supervised Learning (半监督学习)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/self-training-%E8%87%AA%E8%AE%AD%E7%BB%83/">Self-Training (自训练)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/multi-view-learning-%E5%A4%9A%E8%A7%86%E5%9B%BE%E5%AD%A6%E4%B9%A0/">Multi-view Learning (多视图学习)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/active-learning-%E4%B8%BB%E5%8A%A8%E5%AD%A6%E4%B9%A0/">Active Learning (主动学习)</a></li> </ul>