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Method plot

sklearn/calibration.py:1428–1480  ·  view source on GitHub ↗

Plot visualization. Extra keyword arguments will be passed to :func:`matplotlib.pyplot.plot`. Parameters ---------- ax : Matplotlib Axes, default=None Axes object to plot on. If `None`, a new figure and axes is created. name

(self, *, ax=None, name=None, ref_line=True, **kwargs)

Source from the content-addressed store, hash-verified

1426 self.pos_label = pos_label
1427
1428 def plot(self, *, ax=None, name=None, ref_line=True, **kwargs):
1429 """Plot visualization.
1430
1431 Extra keyword arguments will be passed to
1432 :func:`matplotlib.pyplot.plot`.
1433
1434 Parameters
1435 ----------
1436 ax : Matplotlib Axes, default=None
1437 Axes object to plot on. If `None`, a new figure and axes is
1438 created.
1439
1440 name : str, default=None
1441 Name for labeling curve. If `None`, use `estimator_name` if
1442 not `None`, otherwise no labeling is shown.
1443
1444 ref_line : bool, default=True
1445 If `True`, plots a reference line representing a perfectly
1446 calibrated classifier.
1447
1448 **kwargs : dict
1449 Keyword arguments to be passed to :func:`matplotlib.pyplot.plot`.
1450
1451 Returns
1452 -------
1453 display : :class:`~sklearn.calibration.CalibrationDisplay`
1454 Object that stores computed values.
1455 """
1456 self.ax_, self.figure_, name = self._validate_plot_params(ax=ax, name=name)
1457
1458 info_pos_label = (
1459 f"(Positive class: {self.pos_label})" if self.pos_label is not None else ""
1460 )
1461
1462 default_line_kwargs = {"marker": "s", "linestyle": "-"}
1463 if name is not None:
1464 default_line_kwargs["label"] = name
1465 line_kwargs = _validate_style_kwargs(default_line_kwargs, kwargs)
1466
1467 ref_line_label = "Perfectly calibrated"
1468 existing_ref_line = ref_line_label in self.ax_.get_legend_handles_labels()[1]
1469 if ref_line and not existing_ref_line:
1470 self.ax_.plot([0, 1], [0, 1], "k:", label=ref_line_label)
1471 self.line_ = self.ax_.plot(self.prob_pred, self.prob_true, **line_kwargs)[0]
1472
1473 # We always have to show the legend for at least the reference line
1474 self.ax_.legend(loc="lower right")
1475
1476 xlabel = f"Mean predicted probability {info_pos_label}"
1477 ylabel = f"Fraction of positives {info_pos_label}"
1478 self.ax_.set(xlabel=xlabel, ylabel=ylabel)
1479
1480 return self
1481
1482 @classmethod
1483 def from_estimator(

Calls 3

_validate_style_kwargsFunction · 0.90
setMethod · 0.80
_validate_plot_paramsMethod · 0.45