facebookresearch / svinfer
The FORT team has released differentially private Condor data to external researchers in H1 2020. It is known that analyzing DP data via classic statistical models will lead to biased conclusions. We are releasing at-scale statistical models which provide valid inference from DP data.
Summary
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| Main Code: 738 LOC (9 files) = PY (100%) | |||
| Duplication: 5% | |||
| File Size: 0% long (>1000 LOC), 62% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 84% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 73% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (4 components) | ||
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1 year, 7 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: 2020-12-24
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