预测聚类 [英] Predict in Clustering

问题描述

在R语言中，像我们在分类中一样，聚类中是否具有预测功能？
除了比较两个聚类之外，我们还能从R得到的聚类图结果中得出什么结论？

In R language is there a predict function in clustering like the way we have in classification? What can we conclude from the clustering graph result that we get from R, other that comparing two clusters?

推荐答案

聚类不关注预测功能。它只是试图查找似乎相关的对象。这就是为什么没有用于聚类结果的预测功能的原因。

Clustering does not pay attention to prediction capabilities. It just tries to find objects that seem to be related. That is why there is no "predict" function for clustering results.

但是，在许多情况下，基于聚类的学习分类器可以提供更好的性能。为此，您实质上要训练一个分类器以将对象分配给适当的集群，然后使用仅对该集群中的示例进行训练的分类器对其进行分类。当集群是纯集群时，您甚至可以跳过此第二步。

However, in many situations, learning classifiers based on the clusters offers an improved performance. For this, you essentially train a classifier to assign the object to the appropriate cluster, then classify it using a classifier trained only on examples from this cluster. When the cluster is pure, you can even skip this second step.

原因如下：可能存在具有相同标签的多个类型。在完整数据集上训练分类器可能很困难，因为它将尝试同时学习两个聚类。将班级分为两组，并为每组分别训练一个分类器，可以使这项任务变得更加容易。

The reason is the following: there may be multiple types that are classified with the same label. Training a classifier on the full data set may be hard, because it will try to learn both clusters at the same time. Splitting the class into two groups, and training a separate classifier for each, can make the task significantly easier.

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