一种新的谱聚类算法
A Tutorial on Spectral Clustering
摘要：
近年来，谱聚类算法已成为最流行的现代聚类算法之一。它易于实现，可以通过标准线性代数软件有效地求解，并且通常优于传统的聚类算法，如k-means算法。乍一看，谱聚类似乎有点神秘，并且不清楚它为什么工作以及它真正做了什么。本教程的目标是对这些问题给出一些直观的认识。我们描述了不同的图拉普拉斯算子和它们的基本性质，提出了最常见的谱聚类算法，并从零开始通过几种不同的方法推导出这些算法。讨论了不同谱聚类算法的优缺点。
英文摘要：
In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algebra software, and very often outperforms traditional clustering algorithms such as the k-means algorithm. On the first glance spectral clustering appears slightly mysterious, and it is not obvious to see why it works at all and what it really does. The goal of this tutorial is to give some intuition on those questions. We describe different graph Laplacians and their basic properties, present the most common spectral clustering algorithms, and derive those algorithms from scratch by several different approaches. Advantages and disadvantages of the different spectral clustering algorithms are discussed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
