71b1e873e70dca43cd12870d4c0f497015f41970,examples/combine/plot_comparison_combine.py,,,#,106

Before Change

fig, ((ax1, ax2), (ax3, ax4), (ax5, ax6)) = plt.subplots(3, 2, figsize=(15, 25))
X, y = create_dataset(n_samples=1000, weights=(0.1, 0.2, 0.7))

ax_arr = ((ax1, ax2), (ax3, ax4), (ax5, ax6))
for ax, sampler in zip(
    ax_arr,

After Change

from imblearn.pipeline import make_pipeline
from sklearn.svm import LinearSVC

samplers = [SMOTE(random_state=0), SMOTEENN(random_state=0), SMOTETomek(random_state=0)]

fig, axs = plt.subplots(3, 2, figsize=(15, 25))
for ax, sampler in zip(axs, samplers):
    clf = make_pipeline(sampler, LinearSVC()).fit(X, y)

Instances