Repository: scikit-learn/scikit-learn
File: sklearn/inspection/_plot/decision_boundary.py (Python)

Code before:
    xx0 : ndarray of shape (grid_resolution, grid_resolution)
        First output of :func:`meshgrid <numpy.meshgrid>`.

    xx1 : ndarray of shape (grid_resolution, grid_resolution)
        Second output of :func:`meshgrid <numpy.meshgrid>`.

    n_classes : int
        Number of classes if estimator is a classifier, number of unique values in the
        response otherwise.

    response : ndarray of shape (grid_resolution, grid_resolution) or \
            (grid_resolution, grid_resolution, n_classes)
        Values of the response function.

    multiclass_colors : list of str or str, default=None
        Specifies how to color each class when plotting all classes of multiclass
        problem. Ignored for binary problems.
        Possible inputs are:

        * list: list of Matplotlib
          `color <https://matplotlib.org/stable/users/explain/colors/colors.html#colors-def>`_
          strings, of length `n_classes`
        * str: name of :class:`matplotlib.colors.Colormap`
        * None: 'tab10' colormap is used to sample colors if the number of
                classes is less than or equal to 10, otherwise 'gist_rainbow'
                colormap.

        Single color colormaps will be generated from the colors in the list or
        colors taken from the colormap and passed to the `cmap` parameter of
        the `plot_method`.

        .. versionadded:: 1.7

    xlabel : str, default=None
        Default label to place on x axis.

    ylabel : str, default=None
        Default label to place on y axis.

    Attributes
    ----------
    surface_ : matplotlib `QuadContourSet` or `QuadMesh` or list of such objects
        If `plot_method` is 'contour' or 'contourf', `surface_` is
        :class:`QuadContourSet <matplotlib.contour.QuadContourSet>`. If
        `plot_method` is 'pcolormesh', `surface_` is
        :class:`QuadMesh <matplotlib.collections.QuadMesh>`.

    multiclass_colors_ : array of shape (n_classes, 4)
        Colors used to plot each class in multiclass problems.
        Only defined when `n_classes` > 2.


Review comment (suggestion):
nit: we should stick to 2 space indentation in this bullet list.

```suggestion
        * None: 'tab10' colormap is used to sample colors if the number of
          classes is less than or equal to 10, otherwise 'gist_rainbow' colormap.
```

Code after:
    xx0 : ndarray of shape (grid_resolution, grid_resolution)
        First output of :func:`meshgrid <numpy.meshgrid>`.

    xx1 : ndarray of shape (grid_resolution, grid_resolution)
        Second output of :func:`meshgrid <numpy.meshgrid>`.

    n_classes : int
        Expected number of unique classes or labels if `response` was generated by a
        :term:`classifier` or a :term:`clusterer`.

        For :term:`outlier detectors`, `n_classes` should be set to 2 by definition
        (inlier or outlier).

        For :term:`regressors`, `n_classes` should also be set to 2 by convention
        (continuous responses are displayed the same way as unthresholded binary
        responses).

        .. versionadded:: 1.9

    response : ndarray of shape (grid_resolution, grid_resolution) or \
            (grid_resolution, grid_resolution, n_classes)
        Values of the response function.

    multiclass_colors : list of str or str, default=None
        Specifies how to color each class when plotting all classes of
        :term:`multiclass` problems.

        Possible inputs are:

        * list: list of Matplotlib
          `color <https://matplotlib.org/stable/users/explain/colors/colors.html#colors-def>`_
          strings, of length `n_classes`
        * str: name of :class:`matplotlib.colors.Colormap`
        * None: 'tab10' colormap is used to sample colors if the number of
          classes is less than or equal to 10, otherwise 'gist_rainbow' colormap.

        Single color (fading to white) colormaps will be generated from the colors in
        the list or colors taken from the colormap, and passed to the `cmap` parameter
        of the `plot_method`.

        For :term:`binary` problems, this is ignored and `cmap` or `colors` can be
        passed as kwargs instead, otherwise, the default colormap ('viridis') is used.

        .. versionadded:: 1.7
        .. versionchanged:: 1.9
           `multiclass_colors` is now also used when `response_method="predict"`

    xlabel : str, default=None
        Default label to place on x axis.

    ylabel : str, default=None