3444430a2a1488de3b96249e363ff4a8aab8a5dd,examples/over-sampling/plot_comparison_over_sampling.py,,,#,109

Before Change

fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 12))

ax_arr = (ax1, ax2, ax3, ax4)
weights_arr = (
    (0.01, 0.01, 0.98),
    (0.01, 0.05, 0.94),
    (0.2, 0.1, 0.7),

After Change

axs[0].set_title("RandomOverSampler with normal bootstrap")
sampler = RandomOverSampler(smoothed_bootstrap=True, shrinkage=0.2, random_state=0)
plot_resampling(X, y, sampler, ax=axs[1])
axs[1].set_title("RandomOverSampler with smoothed bootstrap")
fig.tight_layout()

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// It looks like more samples are generated with smoothed bootstrap. This is due

Instances