text: #coding: utf-8
  import numpy as np
  from sklearn import datasets, svm, cross_validation
  
  """
  K-fold Cross-validation
  """
  
  digits = datasets.load_digits()
  X_digits = digits.data
  y_digits = digits.target
  
  K = 10
  
  svc = svm.SVC(C=1, kernel='linear')
  
  # KFoldは訓練集合とテスト集合の分割結果のインデックスを返す
  kfold = cross_validation.KFold(len(X_digits), n_folds=K)
  for i, (train_indices, test_indices) in enumerate(kfold):
      print ('%d : Train: %s | test: %s' % (i, len(train_indices), len(test_indices)))
  
  # 分類精度を評価
  scores = cross_validation.cross_val_score(svc, X_digits, y_digits, cv=kfold, n_jobs=-1)
  
  print scores
  print "mean:", np.mean(scores)
  