remove faces pca n_components=2000 that's not shown

breaks with sklearn 0.20 because n_components larger than rank.

Author: amueller

mglearn/plot_pca.py

@@ -94,10 +94,10 @@ def plot_pca_whitening():
 @memory.cache
 def pca_faces(X_train, X_test):
     # copy and pasted from nmf. refactor?
-    # Build NMF models with 10, 50, 100, 500 and 2000 components
+    # Build NMF models with 10, 50, 100, 500 components
     # this list will hold the back-transformd test-data
     reduced_images = []
-    for n_components in [10, 50, 100, 500, 2000]:
+    for n_components in [10, 50, 100, 500]:
         # build the NMF model
         pca = PCA(n_components=n_components)
         pca.fit(X_train)
@@ -126,5 +126,5 @@ def plot_pca_faces(X_train, X_test, image_shape):
 
     # label the top row
     axes[0, 0].set_title("original image")
-    for ax, n_components in zip(axes[0, 1:], [10, 50, 100, 500, 2000]):
+    for ax, n_components in zip(axes[0, 1:], [10, 50, 100, 500]):
         ax.set_title("%d components" % n_components)