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2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ repos:
- id: debug-statements
- id: requirements-txt-fixer
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: "v0.15.14"
rev: "v0.16.5"
hooks:
- id: ruff-format
- repo: local
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4 changes: 3 additions & 1 deletion CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -474,7 +474,9 @@ Expect similar or slightly slower training times due to interactions.
from interpret.version import __version__

# Change this to your custom CDN.
JS_URL = "https://unpkg.com/@interpretml/interpret-inline@{}/dist/interpret-inline.js".format(__version__)
JS_URL = "https://unpkg.com/@interpretml/interpret-inline@{}/dist/interpret-inline.js".format(
__version__
)
set_visualize_provider(InlineProvider(js_url=JS_URL))
```
- EBM has changed initialization parameters:
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13 changes: 9 additions & 4 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -107,12 +107,17 @@ show([logistic_regression_global, decision_tree_global])
If you need to keep your data private, use Differentially Private EBMs (see [DP-EBMs](https://proceedings.mlr.press/v139/nori21a/nori21a.pdf))

```python
from interpret.privacy import DPExplainableBoostingClassifier, DPExplainableBoostingRegressor

dp_ebm = DPExplainableBoostingClassifier(epsilon=1, delta=1e-5) # Specify privacy parameters
from interpret.privacy import (
DPExplainableBoostingClassifier,
DPExplainableBoostingRegressor,
)

dp_ebm = DPExplainableBoostingClassifier(
epsilon=1, delta=1e-5
) # Specify privacy parameters
dp_ebm.fit(X_train, y_train)

show(dp_ebm.explain_global()) # Identical function calls to standard EBMs
show(dp_ebm.explain_global()) # Identical function calls to standard EBMs
```

<br/>
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