Gaussian Mechanism Global DP for SKLearn Pipeline
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评估
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 新手友好度
- 45/100
- Issue 类型
- 功能
- 描述清晰度
- 基本清楚
- 活跃度
- 停滞
- 技术栈
- python, scikit-learn
调研方向
Start with src/pydp/ml/mechanisms/sklearn_pipeline.py and the existing LaplaceMechanism implementation, then review examples/SKLearn_Pipeline/SKLearn_Pipeline_Laplace_Mechanism.ipynb. Compare the Local DP implementation with the requirements for Global DP and verify that GaussianMechanism can be inserted into an sklearn Pipeline as shown; done means the operator is available with the requested usage and a corresponding example works.
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描述
Feature Description
Enabling the use of Gaussian Mechanism for Local DP in SKLean Pipeline. This should be in the form of an "operator" that should be inserted between the layers in SKLearn's Pipeline class.
This is the Global DP Version of the already existing Gaussian Mechanism extension for Local DP mentioned in issue #387.
Additional Context
Current development for the SKLean Pipeline is in branch feature/machine-learning-1.
Preferably, the name of the "operator" imported from PyDP should be called GaussianMechanism. The use should be as seamless and convenient as possible in SKLearn's Pipeline class. For example:
pipe = Pipeline([
('scaler', StandardScaler()),
('nb', GaussianNB()),
('gaussian', GaussianMechanism()),
])
For more examples, please have look at the notebook example of Laplace Mechanism's implementation.
As starting guidance, please refer to the source code for LaplaceMechanism in here.
Note: The examples mentioned above are for Local DP. Laplace Mechanism's LocalDP implementation should provide a good starting point to figure out the Global DP's version.
- 主要语言
- Python
- 星标
- 550
- 派生
- 143
- PR 合并指标
- 30 天内没有已合并 PR
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OpenMined/PyDP 的其他 Issue
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Type: New Feature :heavy_plus_sign:
难度 4/5 3-5 天 新手友好度 45/100
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Type: New Feature :heavy_plus_sign:
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