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Fix incorrect default alternative kwarg and docs in FET detectors #661

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Oct 21, 2022
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7 changes: 7 additions & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
@@ -1,5 +1,12 @@
# Change Log

## v0.10.4
## [v0.10.4](https://github.com/SeldonIO/alibi-detect/tree/v0.10.4) (2022-10-21)
[Full Changelog](https://github.com/SeldonIO/alibi-detect/compare/v0.10.3...v0.10.4)

### Fixed
- Fixed an incorrect default value for the `alternative` kwarg in the `FETDrift` detector ([#661](https://github.com/SeldonIO/alibi-detect/pull/661)).

## v0.10.3
## [v0.10.3](https://github.com/SeldonIO/alibi-detect/tree/v0.10.3) (2022-08-17)
[Full Changelog](https://github.com/SeldonIO/alibi-detect/compare/v0.10.2...v0.10.3)
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2 changes: 1 addition & 1 deletion alibi_detect/cd/fet.py
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ def __init__(
update_x_ref: Optional[Dict[str, int]] = None,
preprocess_fn: Optional[Callable] = None,
correction: str = 'bonferroni',
alternative: str = 'decrease',
alternative: str = 'greater',
n_features: Optional[int] = None,
input_shape: Optional[tuple] = None,
data_type: Optional[str] = None
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4 changes: 2 additions & 2 deletions doc/source/cd/methods/fetdrift.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@
"\n",
"The null hypothesis is $H_0: \\widehat{OR}=1$. In other words, the proportion of 1's to 0's is unchanged between the test and reference distributions, such that the odds of 1's vs 0's is independent of whether the data is drawn from the reference or test distribution. The offline FET detector can perform one-sided or two-sided tests, with the alternative hypothesis set by the `alternative` keyword argument:\n",
"\n",
"- If `alternative='greater'`, the alternative hypothesis is $H_a: \\widehat{OR}>1$ i.e. proportion of 1's versus 0's has increased compared to reference distribution.\n",
"- If `alternative='greater'`, the alternative hypothesis is $H_a: \\widehat{OR}>1$ i.e. proportion of 1's versus 0's has increased compared to the reference distribution.\n",
"- If `alternative='less'`, the alternative hypothesis is $H_a: \\widehat{OR}<1$ i.e. the proportion of 1's versus 0's has decreased compared to the reference distribution.\n",
"- If `alternative='two-sided'`, the alternative hypothesis is $H_a: \\widehat{OR} \\ne 1$ i.e. the proportion of 1's versus 0's has changed compared to the reference distribution.\n",
"\n",
Expand All @@ -56,7 +56,7 @@
"\n",
"Arguments:\n",
"\n",
"* `x_ref`: Data used as reference distribution.\n",
"* `x_ref`: Data used as reference distribution. Note this should be the raw data, for example `np.array([0, 0, 1, 0, 0, 0])`, not the 2x2 contingency table.\n",
"\n",
"Keyword arguments:\n",
"\n",
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