Visualization of confusion matrices with network graphs

The use of network analysis as a means of visualizing the off‐diagonal (misclassified) elements of a confusion matrix is demonstrated, and the potential to use the network graphs as a guide for developing hierarchical classification models is presented. A very brief summary of graph theory is described. This is followed by an explanation and code with examples of how these networks can then be used for visualization of confusion matrices. The use of network graphs to provide insight into differing model performance is also addressed. The use of network analysis to visualize the off‐diagonal (misclassified) elements of a confusion matrix is demonstrated, and the potential to use the network graphs as a guide for developing hierarchical classification models is presented. A brief summary of graph theory is described. This is followed by an explanation and code with examples of how these networks can be used for visualization of confusion matrices. The use of network graphs to provide insight into differing model performance is also addressed.