8000 DOC: fix typos in linear_model.rst (#8868) · scikit-learn/scikit-learn@1de66a0 · GitHub
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DOC: fix typos in linear_model.rst (#8868)
* DOC fix typos in linear_model.rst * Another typo
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doc/modules/linear_model.rst

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@@ -544,8 +544,8 @@ This can be done by introducing `uninformative priors
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<https://en.wikipedia.org/wiki/Non-informative_prior#Uninformative_priors>`__
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over the hyper parameters of the model.
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The :math:`\ell_{2}` regularization used in `Ridge Regression`_ is equivalent
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to finding a maximum a-postiori solution under a Gaussian prior over the
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parameters :math:`w` with precision :math:`\lambda^-1`. Instead of setting
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to finding a maximum a posteriori estimation under a Gaussian prior over the
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parameters :math:`w` with precision :math:`\lambda^{-1}`. Instead of setting
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`\lambda` manually, it is possible to treat it as a random variable to be
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estimated from the data.
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@@ -601,7 +601,7 @@ remaining hyperparameters are the parameters of the gamma priors over
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*non-informative*. The parameters are estimated by maximizing the *marginal
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log likelihood*.
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By default :math:`\alpha_1 = \alpha_2 = \lambda_1 = \lambda_2 = 1.e^{-6}`.
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By default :math:`\alpha_1 = \alpha_2 = \lambda_1 = \lambda_2 = 10^{-6}`.
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.. figure:: ../auto_examples/linear_model/images/sphx_glr_plot_bayesian_ridge_001.png

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