code: '''
   Created on Sat Nov 05 2016
  
   Copyright (c) 2016 Leniel Macaferi's Consulting
  '''
  
  import os
  import pandas as pd
  from sklearn.naive_bayes import GaussianNB
  from sklearn.model_selection import cross_val_score
  
  path = os.path.realpath('..')
  
  # Loading the data used to train
  trainingSet = pd.read_csv(os.path.join(path, '../Data/classification-training.csv'), sep=',', header = None)
  
  classes = trainingSet[trainingSet.columns[22]] # Last column
  features = trainingSet[trainingSet.columns[1:22]] # Columns between indexes 1 to 22
  
  #pd.set_option('display.max_columns', 23)
  #print(features)
  
  classifier = GaussianNB()
  
  scores = cross_val_score(classifier, features, classes, cv = 5)
  
  print(scores)
  
  print("Accuracy: %0.2f (+/- %0.2f)" % (scores.mean(), scores.std() * 2))
apis: sklearn.model_selection.cross_val_score sklearn.naive_bayes.GaussianNB