Chapter 6. Advanced Cluster Analysis

In this chapter, you will learn how to implement the top algorithms for clusters with R. The evaluation/benchmark/measure tools are also provided.

In this chapter, we will cover the following topics:

  • Customer categorization analysis of e-commerce and DBSCAN
  • Clustering web pages and OPTICS
  • Visitor analysis in the browser cache and DENCLUE
  • Recommendation system and STING
  • Web sentiment analysis and CLIQUE
  • Opinion mining and WAVE CLUSTER
  • User search intent and the EM algorithm
  • Customer purchase data analysis and clustering high-dimensional data
  • SNS and clustering graph and network data

Customer categorization analysis of e-commerce and DBSCAN

By defining the density and density measures of data point space, the clusters can ...

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