> For the complete documentation index, see [llms.txt](https://wiki.aig123.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://wiki.aig123.com/ai-wiki/ren-gong-zhi-neng-zhuan-ye-shu-yu-biao/d.md).

# D

**Data (Structured Data, Unstructured Data, Data augmentation)（数据-结构化数据、非结构化数据、数据增强）**

所有机器学习和人工智能项目的最基本要素。

**非结构化数据：**未经处理的原始数据。文本数据是非结构化数据的完美示例，因为它没有格式化为特定功能。

**结构化数据：**以机器学习算法可摄取的方式处理的数据；如果是监督机器学习，则为已标记的、经处理后的数据。

**数据增强：**将内外部来源衍生的新信息添加到数据集的过程（一般通过标注来实现）。

**Decision Tree（决策树）**

监督机器学习算法的一个类别，在此类算法中，数据会根据给定参数或条件进行迭代拆分。

**Deep Blue（深蓝）**

由 IBM 开发的国际象棋游戏计算机，作为全球首个在常规时限内同时战胜了国际象棋游戏和国际象棋比赛卫冕世界冠军的计算机国际象棋游戏系统而闻名。

**Deep Learning (Deep Reinforcement Learning)（深度学习/深度强化学习）**

与特定任务的算法相反，基于学习数据表示的更广泛的机器学习方法系列。深度学习包括监督学习、半监督学习或无监督学习。

**维度（降维、维度灾难）**

**降维：**通过获取一组主变量来减少所考虑的随机变量数量的过程。另请参见特征选择。

**维度灾难：**由于维数越多，可用数据量越稀疏这一事实，在高维空间中分析和组织数据时出现的一种现象。


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