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DOC fix minor typos #23414

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merged 1 commit into from May 19, 2022
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DOC fix minor typos #23414

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4 changes: 2 additions & 2 deletions doc/tutorial/statistical_inference/supervised_learning.rst
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Expand Up @@ -133,7 +133,7 @@ Linear model: from regression to sparsity
.. topic:: Diabetes dataset

The diabetes dataset consists of 10 physiological variables (age,
sex, weight, blood pressure) measure on 442 patients, and an
sex, weight, blood pressure) measured on 442 patients, and an
indication of disease progression after one year::

>>> diabetes_X, diabetes_y = datasets.load_diabetes(return_X_y=True)
Expand Down Expand Up @@ -309,7 +309,7 @@ informative features and set non-informative ones, like feature 2 to 0. Ridge
regression will decrease their contribution, but not set them to zero. Another
penalization approach, called :ref:`lasso` (least absolute shrinkage and
selection operator), can set some coefficients to zero. Such methods are
called **sparse method** and sparsity can be seen as an
called **sparse methods** and sparsity can be seen as an
application of Occam's razor: *prefer simpler models*.

::
Expand Down