title: How to copy training data n times during classification?
body: <p>I have a classification problem with two data-set with 200 and 50 points respectively. Out of these 40 data points are taken as test set. I have chosen kNN as the classifier considering five nearest neighbors.</p>
  
  <pre><code>n_neighbors = 5
  std = 5
  
  # generate data
  
  X0, y0 = make_blobs(n_samples=200, centers=2, n_features=2, cluster_std = std, random_state=42)
  h = .1  # step size in the mesh
  
  X1, y1 = make_blobs(n_samples=50, centers=2, n_features=2, cluster_std = std, random_state=42)
  
  # split into training and test set
  X0_train, X0_test, y0_train, y0_test = train_test_split(X0, y0, test_size=0.2, random_state=42)
  
  X1_train, X1_test, y1_train, y1_test = train_test_split(X1, y1, test_size=0.2, random_state=42)
  </code></pre>
  
  <p>I have to enrich the data in such a way that training data for class 1 is copied 16 times, such that class 1 has the same training size as class 0.</p>
  
  <p>How can I copy the training data sixteen times? I do not have a clue, exactly what copying means here.</p>
  
  <p>Can anyone throw some lines of code to explain the same?</p>