https://terms-en.ai-term-hub.com/zh/tags/standardization/Recent content in Standardization 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/data_preprocessing/Sat, 18 Jul 2026 11:12:36 +0000https://terms-en.ai-term-hub.com/zh/terms/data_preprocessing/<h2 id="definition">Definition</h2> <p>数据预处理是将原始的、非结构化或嘈杂的数据转换为标准化格式的关键任务，使机器学习模型能够有效处理这些数据。此阶段通常包括数据清洗、归一化、编码和特征缩放等操作。</p> <h3 id="summary">Summary</h3> <p>将原始数据转换为干净、一致的格式，以便机器学习算法使用的过程。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>数据清洗</li> <li>归一化</li> <li>编码</li> <li>特征缩放</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>对数值输入进行缩放以促进神经网络收敛</li> <li>将文本标签转换为数值向量</li> <li>对传感器数据中的缺失值进行插补</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.preprocessing <span style="color:#f92672">import</span> StandardScaler </span></span><span style="display:flex;"><span>scaler <span style="color:#f92672">=</span> StandardScaler() </span></span><span style="display:flex;"><span>data_scaled <span style="color:#f92672">=</span> scaler<span style="color:#f92672">.</span>fit_transform(raw_data) </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/data_augmentation-%E6%95%B0%E6%8D%AE%E5%A2%9E%E5%BC%BA/">data_augmentation (数据增强)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/feature_selection-%E7%89%B9%E5%BE%81%E9%80%89%E6%8B%A9/">feature_selection (特征选择)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/normalization-%E5%BD%92%E4%B8%80%E5%8C%96/">normalization (归一化)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/one_hot_encoding-%E7%8B%AC%E7%83%AD%E7%BC%96%E7%A0%81/">one_hot_encoding (独热编码)</a></li> </ul>