text: import numpy as np 
  import json, pickle
  import pandas as pd
  from sklearn.decomposition import PCA
  from sklearn.model_selection import train_test_split
  from sklearn.naive_bayes import BernoulliNB
  from sklearn.pipeline import make_pipeline
  
  # NOTE: Make sure that the outcome column is labeled 'target' in the data file
  g=json.load(open('test_tpot_classifier.json'))
  tpot_data=np.array(g['labels'])
  features=np.array(g['data'])
  
  training_features, testing_features, training_target, testing_target = \
              train_test_split(features, tpot_data, random_state=None)
  
  # Average CV score on the training set was: 0.5583333333333333
  exported_pipeline = make_pipeline(
      PCA(iterated_power=5, svd_solver="randomized"),
      BernoulliNB(alpha=100.0, fit_prior=True)
  )
  
  exported_pipeline.fit(training_features, training_target)
  print('saving classifier to disk')
  f=open('test_tpot_classifier.pickle','wb')
  pickle.dump(exported_pipeline,f)
  f.close()
  