DOC More details about the attributes in MinMaxScaler #13029
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| @@ -210,6 +210,11 @@ class MinMaxScaler(BaseEstimator, TransformerMixin): | |||
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| where min, max = feature_range. | |||
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| The transformation is calculated as:: | |||
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This seems to be talking about transformation of the training data? Shouldn't these formulas include the _ attributes?
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Yes, the goal is to help users understand the algorithm (users can easily extend it to new data)
I don't use _ attributes to keep consistent with the way we define the transformation:
The transformation is given by::
X_std = (X - X.min(axis=0)) / (X.max(axis=0) - X.min(axis=0))
X_scaled = X_std * (max - min) + min
where min, max = feature_range.``
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Yes, I think that is more accessible
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Yes, I think that is more accessible
So what's your suggestion here?
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I am worried that if we start to define this for the NB: I am not against the changes but I was wondering if you have any thoughts. @qinhanmin2014 did you have experiences where users were lacking this information in the docstring? |
My intention here is to explain the attribute |
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OK I see. So I am fine with the changes then. |
…-learn#13029)" This reverts commit 65435bf.
…-learn#13029)" This reverts commit 65435bf.
Help users to understand the attribute without reading the code.