Practical Guide To Principal Component Methods ... (2025)

: Those who need to analyze large multivariate datasets for research or business but prefer practical implementation over theoretical derivation.

: The book heavily utilizes the author's own factoextra R package , which creates elegant, ggplot2 -based graphs to help interpret results. Practical Guide To Principal Component Methods ...

: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA) for datasets with both continuous and categorical variables. : Those who need to analyze large multivariate

: Hierarchical Clustering on Principal Components (HCPC), which combines dimensionality reduction with clustering techniques. Who Should Read It which creates elegant

: Principal Component Analysis (PCA) for quantitative variables.