Using Graphs to Analyze High-Dimensional Classifiers
نویسندگان
چکیده
In this paper we present a method to extract qualitative information from any classi cation model that uses decision regions to generalize (e.g. neural nets, SVMs, graphical models etc) that is independent on the dimensionality of the data and model. The qualitative information can be directly used to analyze the classi cation strategies employed by a model, and also to directly compare strategies across di erent models. We apply the method to compare between two types of classi ers using real-world high-dimensional data.
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