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DOC avoid clipping axis name in example #827

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Apr 13, 2021
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DOC avoid clipping axis name in example #827

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5 changes: 5 additions & 0 deletions examples/over-sampling/plot_shrinkage_effect.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,7 @@
ax.add_artist(class_legend)
ax.set_xlabel("Feature #1")
_ = ax.set_ylabel("Feature #2")
plt.tight_layout()

# %%
# Now, we will use a :class:`~imblearn.over_sampling.RandomOverSampler` to
Expand All @@ -61,6 +62,7 @@
ax.add_artist(class_legend)
ax.set_xlabel("Feature #1")
_ = ax.set_ylabel("Feature #2")
plt.tight_layout()
# %%
# We observe that the minority samples are less transparent than the samples
# from the majority class. Indeed, it is due to the fact that these samples
Expand All @@ -79,6 +81,7 @@
ax.add_artist(class_legend)
ax.set_xlabel("Feature #1")
_ = ax.set_ylabel("Feature #2")
plt.tight_layout()

# %%
# In this case, we see that the samples in the minority class are not
Expand All @@ -97,6 +100,7 @@
ax.add_artist(class_legend)
ax.set_xlabel("Feature #1")
_ = ax.set_ylabel("Feature #2")
plt.tight_layout()

# %%
# Increasing the value of `shrinkage` will disperse the new samples. Forcing
Expand All @@ -112,6 +116,7 @@
ax.add_artist(class_legend)
ax.set_xlabel("Feature #1")
_ = ax.set_ylabel("Feature #2")
plt.tight_layout()

# %%
# Therefore, the `shrinkage` is handy to manually tune the dispersion of the
Expand Down