Fix bullet point lists.

Author: C-BdB

examples/regression/2-advanced-analysis/plot_conditional_coverage.py

@@ -191,13 +191,12 @@ def sin_with_controlled_noise(
 # :func:`~mapie.metrics.regression_ssc_score` and :func:`~mapie.metrics.hsic`.
 #
 # - SSC (Size Stratified Coverage): This measures the maximum violation
-# of coverage by grouping intervals by width and computing coverage for
-# each group. An adaptive method has a maximum violation close to the global
-# coverage. Among the four methods, CV+ performs the best.
-#
-# HSIC (Hilbert-Schmidt Independence Criterion): This computes the
-# correlation between coverage and interval size. A value of 0 indicates
-# independence between the two.
+#   of coverage by grouping intervals by width and computing coverage for
+#   each group. An adaptive method has a maximum violation close to the global
+#   coverage. Among the four methods, CV+ performs the best.
+# - HSIC (Hilbert-Schmidt Independence Criterion): This computes the
+#   correlation between coverage and interval size. A value of 0 indicates
+#   independence between the two.
 #
 # It's important to note that CV+ with the absolute residual score
 # calculates constant intervals, which are not adaptive. Therefore,

examples/regression/2-advanced-analysis/plot_cqr_symmetry_difference.py

@@ -124,9 +124,10 @@
 plt.show()
 
 ##############################################################################
-# The symmetric intervals (``symmetric_correction=True``) use a combined set of residuals
-# for both bounds, while the asymmetric intervals (``symmetric_correction=False``)
-# use distinct residuals for each bound, allowing for more flexible and
-# accurate intervals that reflect the heteroscedastic nature of the data.
-# The resulting effective coverages demonstrate the theoretical guarantee of
-# the target coverage level ``confidence_level``.
+# The symmetric intervals (``symmetric_correction=True``) use a combined set of
+# residuals for both bounds, while the asymmetric intervals
+# (``symmetric_correction=False``) use distinct residuals for each bound,
+# allowing for more flexible and accurate intervals that reflect the
+# heteroscedastic nature of the data. The resulting effective coverages
+# demonstrate the theoretical guarantee of the target coverage level
+# ``confidence_level``.