ENH Improve speed plot_permutation_tests_for_classification.py (scikit-learn#21649)

Sven Eschlbeck · glemaitre · commit aba14c8baabf · 2021-11-22T11:02:41.000+01:00
diff --git a/examples/model_selection/plot_permutation_tests_for_classification.py b/examples/model_selection/plot_permutation_tests_for_classification.py
@@ -27,14 +27,14 @@
 y = iris.target
 
 # %%
-# We will also generate some random feature data (i.e., 2200 features),
+# We will also generate some random feature data (i.e., 20 features),
 # uncorrelated with the class labels in the iris dataset.
 
 import numpy as np
 
-n_uncorrelated_features = 2200
+n_uncorrelated_features = 20
 rng = np.random.RandomState(seed=0)
-# Use same number of samples as in iris and 2200 features
+# Use same number of samples as in iris and 20 features
 X_rand = rng.normal(size=(X.shape[0], n_uncorrelated_features))
 
 # %%
