Concrete ML
WebsiteLibrariesProducts & ServicesDevelopersSupport
0.3
0.3
  • What is Concrete ML?
  • Getting Started
    • Installation
    • Key Concepts
  • Built-in Models
    • Linear Models
    • Tree-based Models
    • Neural Networks
    • Examples
  • Deep Learning
    • Using Torch
    • Using ONNX
    • Examples
    • Debugging Models
  • Advanced topics
    • Quantization
    • Pruning
    • Production Deployment
    • Compilation
    • More about ONNX
    • FHE Op-graphs
    • Using Hummingbird
    • Using Skorch
  • Developer Guide
    • Set Up the Project
    • Set Up Docker
    • Documentation
    • Support and Issues
    • Contributing
    • API
Powered by GitBook

Libraries

  • TFHE-rs
  • Concrete
  • Concrete ML
  • fhEVM

Developers

  • Blog
  • Documentation
  • Github
  • FHE resources

Company

  • About
  • Introduction to FHE
  • Media
  • Careers
On this page
  • Concrete-ML models
  • Comparison of classifiers
  • Kaggle competition

Was this helpful?

Export as PDF
  1. Built-in Models

Examples

PreviousNeural NetworksNextUsing Torch

Last updated 2 years ago

Was this helpful?

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

Model
Dataset
Metric
Clear
Quantized
FHE

Linear Regression

Synthetic 1D

R2

0.876

0.863

0.863

Logistic Regression

Synthetic 2D with 2 classes

accuracy

0.90

0.875

0.875

Poisson Regression

mean Poisson deviance

0.61

0.60

0.60

Gamma Regression

mean Gamma deviance

0.45

0.45

0.45

Tweedie Regression

mean Tweedie deviance (power=1.9)

33.42

34.18

34.18

Decision Tree

precision score

0.95

0.97

0.97*

XGBoost

MCC

0.48

0.52

0.52*

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

Concrete-ML models

Comparison of classifiers

Kaggle competition

LinearRegression.ipynb
LogisticRegression.ipynb
PoissonRegression.ipynb
DecisionTreeClassifier.ipynb
XGBClassifier.ipynb
GLMComparison.ipynb
ClassifierComparison.ipynb
KaggleTitanic.ipynb
OpenML insurance (freq)
OpenML insurance (sev)
OpenML insurance (sev)
OpenML spams
Diabetes