The Hot Path Belongs to GBDTs, Agents Own the Cold Path: A Payment-Fraud Benchmark
Evolving story · 1 updatesAgents vs. GBDTs in Payment-Fraud DetectionTimeline → 30-second summary
A benchmark study compares Gradient Boosted Decision Trees (GBDTs) and AI agents for payment-fraud detection, highlighting GBDTs' efficiency in high-throughput scenarios and agents' superiority in complex, low-frequency cases.
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A reproducible benchmark on latency, cost, and reproducibility, and where agents actually earn their keep.
The post The Hot Path Belongs to GBDTs, Agents Own the Cold Path: A Payment-Fraud Benchmark appeared first on Towards Data Science.
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