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Hey, In the old docs of sklearn for normalize parameter it was written:
This parameter is ignored when fit_intercept is set to False. If True, the regressors X will be normalized before regression by subtracting the mean and dividing by the l2-norm.
And fit_intercept defaults to True in the newer version of sklearn. So can we directly remove normalize argument? I think it wont effect the functionality because it is still normalizing.
Describe the bug
The following will fail for scikit-learn version 1.2:
Docs for 1.0: https://scikit-learn.org/1.0/modules/generated/sklearn.linear_model.LinearRegression.html?highlight=linearregression#sklearn.linear_model.LinearRegression
Docs for 1.2: https://scikit-learn.org/1.2/modules/generated/sklearn.linear_model.LinearRegression.html?highlight=linearregression#sklearn.linear_model.LinearRegression
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