Visualizing Dimension Reduction Analysis Outputs

Visualization of PCA, CA, MCA, FAMD, MFA and HMFA.

Extract and visualize the eigenvalues/variances of dimensions

Visualize Correspondence Analysis

Visualize the contributions of row/column elements

Visualize the quality of representation of rows/columns

Visualize Factor Analysis of Mixed Data

Visualize Hierarchical Multiple Factor Analysis

Visualize Multiple Correspondence Analysis

Visualize Multiple Factor Analysis

Visualize Principal Component Analysis

Extracting Data from Dimension Reduction Analysis Outputs

Extracting data from the output of PCA, CA, MCA, FAMD, MFA and HMFA.

Subset and summarize the output of factor analyses

Extract the results for rows/columns - CA

Extract the results for individuals and variables - FAMD

Extract the results for individuals/variables/group/partial axes - HMFA

Extract the results for individuals/variables - MCA

Extract the results for individuals/variables/group/partial axes - MFA

Extract the results for individuals/variables - PCA

Clustering

Computing and visualizing clustering

Enhanced Distance Matrix Computation and Visualization

Visual enhancement of clustering analysis

Visualize Clustering Results

Enhanced Visualization of Dendrogram

Plot Model-Based Clustering Results using ggplot2

Dertermining and Visualizing the Optimal Number of Clusters

Visualize Silhouette Information from Clustering

Assessing Clustering Tendency

Computes Hierarchical Clustering and Cut the Tree

Hierarchical k-means clustering

Data

Data sets included in factoextra and used in examples.

Athletes' performance in decathlon

House tasks contingency table

A dataset containing clusters of multiple shapes

Poison

Others

Add supplementary data to a plot

Print method for an object of class factoextra