text: 
  #semeion.py
  
  from numpy import *
  from matplotlib.pyplot import *
  import pandas as pd
  from sklearn.svm import SVC
  
  df = pd.read_csv('semeion.data', sep=' ', header=None).as_matrix()
  
  X = df[:, 0:256]
  y = df[:, 256:266].argmax(1)
  
  index = arange(len(y))
  random.shuffle(index)
  
  N = 1000
  train_index = index[:N]
  test_index  = index[N:]
  
  clf = SVC()
  clf.fit(X[train_index], y[train_index])
  
  print clf.score(X[test_index], y[test_index])