– Covers specialized techniques such as:
– Teaches how to measure the "goodness" of your results. This includes assessing clustering tendency, determining the optimal number of clusters , and using validation statistics to ensure patterns aren't just random noise. Practical Guide to Cluster Analysis in R. Unsup...
: The author developed the factoextra R package specifically to help users create ggplot2 -based visualizations of multivariate data and clustering results. – Covers specialized techniques such as: – Teaches
The book is organized into five distinct parts, each focusing on a critical phase of the clustering workflow: determining the optimal number of clusters
: Every chapter concludes with systematic R labs that work through real-world applications, such as analyzing gene expression data or market segments.