In a benchmark of eight graph datasets, the measures AbsSupDif and Sup rank discriminative subgraphs best, while widely used measures such as GR, Acc, and InfGain perform worse, and footprint-based clustering reduces the number of patterns with comparable F1.
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Pattern-Based Graph Classification: Comparison of Quality Measures and Importance of Preprocessing
In a benchmark of eight graph datasets, the measures AbsSupDif and Sup rank discriminative subgraphs best, while widely used measures such as GR, Acc, and InfGain perform worse, and footprint-based clustering reduces the number of patterns with comparable F1.