Models are also compatible with some of scikit-learn's main workflows, such as Pipeline() or GridSearch().
We can clearly observe the impact of quantization over the decision boundaries in the FHE model, separating the initial lines into broken lines with steps. However, this does not change the overall score as both models output the same accuracy (90%).
In fact, the quantization process may sometimes create some artifacts that could lead to a decrease in performance. Still, the impact of those artifacts is often minor when considering linear models as FHE models reach similar scores as their equivalent clear ones.