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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