code: def silhouette(ax=None):
      X, y = make_blobs(
          centers=12, n_samples=1000, n_features=16, shuffle=True
      )
  
      viz = SilhouetteVisualizer(KMeans(9), ax=ax)
      viz.fit(X)
      viz.finalize()
  
      return viz
  
imports: import os
  import sys
  import argparse
  import numpy
  import matplotlib.pyplot
  from yellowbrick.regressor import AlphaSelection
  from yellowbrick.regressor import ResidualsPlot
  from yellowbrick.regressor import PredictionError
  from yellowbrick.cluster import KElbowVisualizer
  from yellowbrick.cluster import SilhouetteVisualizer
  from yellowbrick.cluster import InterclusterDistance
  from yellowbrick.classifier import PrecisionRecallCurve
  from yellowbrick.classifier import ClassPredictionError
  from yellowbrick.classifier import DiscriminationThreshold
  from yellowbrick.datasets import load_spam, load_concrete, load_game
  from sklearn.cluster import KMeans
  from sklearn.datasets import make_blobs
  from sklearn.naive_bayes import GaussianNB
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.linear_model import LogisticRegression, Lasso, LassoCV, Ridge
label_desc: Use image node_id 12 for calling a global function with example usage: silhouette(ax) and returns: viz