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Examples

The following table summarizes the various examples in this section, along with their accuracies.

Model

Dataset

Metric

Clear

Quantized

FHE

Linear Regression

Synthetic 1D

0.876

0.863

Logistic Regression

Synthetic 2D with 2 classes

accuracy

0.90

0.875

Poisson Regression

OpenML insurance (freq)

mean Poisson deviance

0.61

0.60

Gamma Regression

OpenML insurance (sev)

mean Gamma deviance

0.45

Tweedie Regression

OpenML insurance (sev)

mean Tweedie deviance (power=1.9)

33.42

34.18

Decision Tree

OpenML spams

precision score

0.95

0.97

0.97*

XGBoost

Diabetes

MCC

0.48

0.52

0.52*

A * means that FHE accuracy was calculated on a subset of the validation set.

Concrete-ML models

LinearRegression.ipynb
LogisticRegression.ipynb
PoissonRegression.ipynb
DecisionTreeClassifier.ipynb
XGBClassifier.ipynb
GLMComparison.ipynb

Comparison of classifiers

ClassifierComparison.ipynb

Kaggle competition

KaggleTitanic.ipynb