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Merge pull request #425 from josecaloca/patch-1
fix: remove incorrect ConstantThreshold from UnivariateDriftCalculator
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nannyml/drift/univariate/calculator.py

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@@ -118,10 +118,10 @@ def __init__(
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{
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'kolmogorov_smirnov': StandardDeviationThreshold(std_lower_multiplier=None),
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'jensen_shannon': ConstantThreshold(upper=0.1),
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'jensen_shannon': StandardDeviationThreshold(std_lower_multiplier=None),
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'wasserstein': StandardDeviationThreshold(std_lower_multiplier=None),
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'hellinger': ConstantThreshold(upper=0.1),
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'l_infinity': ConstantThreshold(upper=0.1)
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'hellinger': StandardDeviationThreshold(std_lower_multiplier=None),
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'l_infinity': StandardDeviationThreshold(std_lower_multiplier=None),
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}
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A dictionary allowing users to set a custom threshold for each method. It links a `Threshold` subclass
@@ -130,10 +130,10 @@ def __init__(
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will be applied. The default method thresholds are as follows:
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- `kolmogorov_smirnov`: `StandardDeviationThreshold(std_lower_multiplier=None)`
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- `jensen_shannon`: `ConstantThreshold(upper=0.1)`
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- `jensen_shannon`: `StandardDeviationThreshold(std_lower_multiplier=None)`
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- `wasserstein`: `StandardDeviationThreshold(std_lower_multiplier=None)`
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- `hellinger`: `ConstantThreshold(upper=0.1)`
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- `l_infinity`: `ConstantThreshold(upper=0.1)`
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- `hellinger`: `StandardDeviationThreshold(std_lower_multiplier=None)`
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- `l_infinity`: `StandardDeviationThreshold(std_lower_multiplier=None)`
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The `chi2` method does not support custom thresholds for now. Additional research is required to determine
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how to transition from its current p-value based implementation.

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