Using graphs to analyze high-dimensional classifiers
Ofer Melnik, Jordan B. Pollack · 2000
We present a method to extract qualitative information from any classification model that uses decision regions, independent on the dimensionality of the data and model. The qualitative information can be directly used to analyze the classification strategies employed by a model, and also to directly compare strategies across different models. We apply the method to compare between two types of classifiers using real-world high-dimensional data.