监管学习的常见例子包括将电子邮件消息分类为垃圾邮件，根据类别标记网页，以及识别手写输入。
Common examples of supervised learning include classifying E-mail messages as spam, labeling Web pages according to their genre, and recognizing handwriting.
该文件在信息自由法的支持下公开发布，所记录的泄漏事件被监管者分类为“重大”或“严重”，这些泄漏的石油如果遇火燃烧则会造成重大人员伤亡。
The documents, released under freedom of information legislation, record leaks classed by the regulator as "major" or "significant", which, if ignited, could cause many deaths.
创建监管学习程序需要使用许多算法，最常见的包括神经网络、Support Vector Machines (SVMs)和Naive Bayes分类程序。
Many algorithms are used to create supervised learners, the most common being neural networks, Support Vector Machines (SVMs), and Naive Bayes classifiers.
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