title: plot_confusion_matrix without estimator
body: <p>I'm trying to use plot_confusion_matrix,</p>
  
  <pre><code>from sklearn.metrics import confusion_matrix
  
  y_true = [1, 1, 0, 1]
  y_pred = [1, 1, 0, 0]
  
  confusion_matrix(y_true, y_pred)
  </code></pre>
  
  <p>Output:</p>
  
  <pre><code>array([[1, 0],
         [1, 2]])
  </code></pre>
  
  <p>Now, while using the followings; using 'classes' or without 'classes'</p>
  
  <pre><code>from sklearn.metrics import plot_confusion_matrix
  
  plot_confusion_matrix(y_true, y_pred, classes=[0,1], title='Confusion matrix, without normalization')
  </code></pre>
  
  <p>or</p>
  
  <pre><code>plot_confusion_matrix(y_true, y_pred, title='Confusion matrix, without normalization')
  </code></pre>
  
  <p>I expect to get similar output like this except the numbers inside,</p>
  
  <p><a href="https://i.stack.imgur.com/15fyL.png" rel="noreferrer"><img src="https://i.stack.imgur.com/15fyL.png" alt="enter image description here"></a></p>
  
  <p>Plotting simple diagram, it should not require the estimator.</p>
  
  <p>Using mlxtend.plotting, </p>
  
  <pre><code>from mlxtend.plotting import plot_confusion_matrix
  import matplotlib.pyplot as plt
  import numpy as np
  
  binary1 = np.array([[4, 1],
                     [1, 2]])
  
  fig, ax = plot_confusion_matrix(conf_mat=binary1)
  plt.show()
  </code></pre>
  
  <p>It provides same output.</p>
  
  <p>Based on <a href="https://scikit-learn.org/stable/modules/generated/sklearn.metrics.plot_confusion_matrix.html" rel="noreferrer">this</a></p>
  
  <p>it requires a classifier,</p>
  
  <pre><code>disp = plot_confusion_matrix(classifier, X_test, y_test,
                                   display_labels=class_names,
                                   cmap=plt.cm.Blues,
                                   normalize=normalize)
  </code></pre>
  
  <p><strong>Can I plot it without a classifier?</strong></p>