无监管学习

Unsupervised learning

以上为机器翻译结果，快速获取精准的人工翻译结果，建议选择有道人工翻译

1
无监管学习的任务是发挥数据的意义，而不管数据的正确与否。
Unsupervised learning, as you might guess, is tasked with making sense of data without any examples of what is correct or incorrect.
2
无监管学习的常见方法包括k - Means、分层集群和自组织地图。
Common approaches to unsupervised learning include k-Means, hierarchical clustering, and self-organizing maps.
3
我将重点讨论其中最常用的两个—监管和无监管学习—因为它们是Mahout支持的主要功能。
I'll focus on the two most commonly used ones - supervised and unsupervised learning - because they are the main ones supported by Mahout.

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