【术语记录】机器学习

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• 实例：要对其进行预测的事物。例如，实例可以是一个网页，您希望将其分类为“与猫相关”或“与猫无关”。
• 标签：预测任务的答案，它可以是由机器学习系统生成的答案，也可以是训练数据中提供的正确答案。例如，某个网页的标签可能是“与猫相关”。
• 特征：预测任务中使用的实例的属性。例如，某个网页可能具有“包含字词‘猫’”这一特征。特征列：一组相关特征，例如用户可能居住的所有国家/地区的集合。样本的特征列中可能包含一个或多个特征。
• 特征列是 Google 专用的术语。特征列在 Yahoo/Microsoft 使用的 VM 系统中被称为“命名空间”或场。
• 样本：一个实例（及其特征）和一个标签。模型：预测任务的统计表示法。您使用样本训练一个模型，然后使用该模型进行预测。
• 指标：您关心的一个数值。也许（但不一定）可以直接得到优化。
• 目标：算法尝试优化的一种指标。
• 管道：机器学习算法的基础架构。管道包括从前端收集数据、将数据放入训练数据文件、训练一个或多个模型以及将模型运用到生产环境。
• 点击率：点击广告中的链接的网页访问者所占的百分比。

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