title: Obtaining a checkerboard pattern using make_classification
body: <p>I am trying to generate a data set by making a function  <code>X,y = make_data(n_instances, n_classes, n_squares)</code> I know that for this, I should use the sci-kit function <code>make_classification()</code>. While I have a basic understanding of this function, I am also asked to produce the data in a checkerboard pattern (the <code>n_squares</code> parameter here referring to the number of squares per axes ie: <code>n_squares=5</code> means a 5*5 pattern on the checkerboard) and this is where I am lost. Can anyone point me in the right direction to produce a desired pattern from <code>make_classification()</code>? I understand that <code>n_samples=n_instances</code> and obviously <code>n_class=n_class</code>, the matrix must have two columns so I am guessing <code>n_informative=2</code> however I am not sure which values to assign to other parameters in order to obtain the chekcerboard pattern.
  Currently, this is what I have</p>
  <pre><code>from sklearn.datasets import make_classification
  def make_data(n_instances, n_classes, n_squares):
      X,y = make_classification(
          n_samples=n_instances, 
          n_informative=2,
          n_redundant=0,
          n_classes=n_classes, 
          n_clusters_per_class=1,
          flip_y=0,
          shuffle=False,
          class_sep=2,
      )
      return X,y
  </code></pre>