Logistic Regression with Homomorphic Encryption
python3 >= 3.5
virtualenv or python3-venv
Packages needed for generating the synthetic datasets are automatically installed in a virtual environment within $HE_SAMPLES/build/examples/logistic-regression/datasets/.
cd $HE_SAMPLES/build/examples/logistic-regression
./lr_test--data: Dataset name. Default is lrtest_mid. There are four different synthetic datasets available for testing, which are automatically generated during build time.
| Name | Features | # Samples |
|---|---|---|
| lrtest_small | 40 | 500 |
| lrtest_mid | 80 | 2000 |
| lrtest_large | 120 | 10000 |
| lrtest_xlarge | 200 | 50000 |
-poly_modulus_degree: Polynomial modulus degree, which determines the encoding slot count (half of the parameter) and encryption security level. Default is 8192, and recommended size is {4096, 8192, 16384}, and must be a power of 2, with full range of [1024, 32768].
--docompare: Compare the HE logistic regression inference result with non-HE inference for validation purposes. Default is false.
There are two example data preparation ipython notebooks in datasets folder.