awslabs / sagemaker-graph-fraud-detection
Use Amazon SageMaker and Deep Graph Library (DGL) for Fraud Detection in Networks
Summary
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| Main Code: 2,164 LOC (28 files) = PY (69%) + YAML (29%) + YML (<1%) + IN (<1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 16 LOC (2); Other: 1,231 LOC (9); |
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| Duplication: 7% | |||
| File Size: 0% long (>1000 LOC), 73% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 58% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 78% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (10 components) | ||
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1 year, 9 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2021-05-18
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