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Boosting Graph Neural Networks with getML: Automated Feature Engineering for Superior Model Performance

Graph Neural Networks (GNNs) excel at modeling complex data but do require feature engineering. This article shows how integrating getML's FastProp automates this process, boosting accuracy to 92.5% on the CORA dataset—surpassing the 90.16% benchmark. This approach simplifies implementation, reduces manual effort, and ensures consistent performance across a wide range of neural architectures, making it a valuable tool for data scientists for building consistent and high-performing models with minimal effort.