Practical Guide to Cluster Analysis in R，作者：Alboukadel Kassambara，出版社：Alboukadel Kassambara  出版社：STHDA
书籍页数：180页 书籍格式：PDF
   附上书籍简介：
     网址链接：http://www.sthda.com/english/download/3-ebooks/9-practical-guide-to-cluster-analysis-in-r
     Large amounts of data are collected every day from satellite images, bio-medical, security, marketing, web search, geo-spatial or other automatic equipment. Mining knowledge from these big data far exceeds human’s abilities.
Clustering is one of the important data mining methods for discovering knowledge in multidimensional data. The goal of clustering is to identify pattern or groups of similar objects within a data set of interest.
In the litterature, it is referred as “pattern recognition” or “unsupervised machine learning” - “unsupervised” because we are not guided by a priori ideas of which variables or samples belong in which clusters. “Learning” because the machine algorithm “learns” how to cluster.
Cluster analysis is popular in many fields, including:

• In cancer research for classifying patients into subgroups according their gene expression profile. This can be useful for identifying the molecular profile of patients with good or bad prognostic, as well as for understanding the disease.
  
• In marketing for market segmentation by identifying subgroups of customers with similar profiles and who might be receptive to a particular form of advertising.
  
• In City-planning for identifying groups of houses according to their type, value and location.