Rodriguez A, Laio A. Clustering by fast search and find of density peaks[J]. Science, 2014, 344(6191): 1492-1496.基于这篇文章实现的最基本的密度聚类的算法，具体请看我博客中的相关文章http://blog.csdn.net/kryolith/article/details/39832573
This book is about high availability (HA) clustering on Linux, a subject that can be overwhelming to administrators who are new to the subject. Although much documentation is already available on the subject, I felt a need to write this book anyway.
We formulate a discrete optimization problem that leads to a simple and informative derivation of a widely used class of spectral clustering algorithms. Regarding the algorithms as attempting to bi-partition a weighted graph with N vertices, our der
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 algorit
Key Features Unleash the power of operating Docker Swarm, Docker Machine and Docker Compose together. Get to grips with Docker Swarm, one of the key components of the Docker ecosystem A comprehensive guide that focuses on Swarm, a super-easy orchest
This is a selection from the notes that I have used in teaching programming courses at SGI and Adobe over the last 10 years. (Some of the material goes back even further to the courses I taught in the 80s at Polytechnic University.) Data clustering
Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this reflects its bro
