Locally differentially Private Decision Tree (LPDT)
This repository implements LPDT, the Locally differentially Private Decision Tree described in the paper Decision Tree for Locally Private Estimation with Public Data accepted for NeurIPS 2023. The implementation is based on pure Python with the following required packages:
- Scikit-learn
- NumPy
- Numba
- Scipy
Contents
Installation
Via PyPI
pip install LPDT
Via GitHub
pip install git+https://github.com/Karlmyh/LPDT.git
Manual Install
git clone git@github.com:Karlmyh/LPDT.git
cd LPDT
python setup.py install
Demo
See simulation.py for a demo of the use of the class.
References
- Decision Tree for Locally Private Estimation with Public Data (NeurIPS 2023)
Metadata
Release files for LPDT 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| LPDT-0.0.2.tar.gz | 10.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| LPDT-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.2 kB
Release files / LPDT-0.0.2.tar.gz
| Download URL | LPDT-0.0.2.tar.gz |
|---|---|
| Size | 10.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
26195a24e7055950ae0ae81f32be36053786e685248aaccb64cefd3414da8f19
|
|
BLAKE2b-256 checksum How to use checksums |
52cfde7bac5b183ef836c526eadd554fe830f97c57e376c33eca7abdd51955a9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / LPDT-0.0.2-py3-none-any.whl
| Download URL | LPDT-0.0.2-py3-none-any.whl |
|---|---|
| Size | 12.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
06771da99b67a6229d0d22286385e4d29898462eb743c3b217ff54a7343ac15e
|
|
BLAKE2b-256 checksum How to use checksums |
3e3edeb3438400e1564dcf004a9a752a3c2501974a5ef73dfa0aec38efea1956
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|