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turning back docs
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Juan Rocha committed Oct 7, 2024
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Expand Up @@ -86,13 +86,13 @@ naml = naiveautoml.NaiveAutoML(scoring="accuracy", passive_scorings=["neg_log_lo
You can also pass a custom scoring function through a dictionary:

```python
scorer = {
scorer = make_scorer(**{
"name": "accuracy",
"score_func": lambda y, y_pred: np.count_nonzero(y == y_pred).mean(),
"greater_is_better": True,
"needs_proba": False,
"needs_threshold": False
}
})
naml = naiveautoml.NaiveAutoML(scoring=scorer)
```

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