数据挖掘中分类和聚类的区别? [英] Difference between classification and clustering in data mining?

问题描述

谁能解释一下数据挖掘中分类和聚类的区别?

Can someone explain what the difference is between classification and clustering in data mining?

如果可以，请举出两者的例子来理解主要思想.

If you can, please give examples of both to understand the main idea.

推荐答案

通常，在分类中，您有一组预定义的类，并且想知道新对象属于哪个类.

In general, in classification you have a set of predefined classes and want to know which class a new object belongs to.

聚类尝试对一组对象进行分组，并找出这些对象之间是否存在某些关系.

Clustering tries to group a set of objects and find whether there is some relationship between the objects.

在机器学习的上下文中，分类是监督学习聚类是无监督学习.

In the context of machine learning, classification is supervised learning and clustering is unsupervised learning.

另请参阅分类和<维基百科上的 href="http://en.wikipedia.org/wiki/Cluster_analysis" rel="noreferrer">聚类.

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