KNN main programme

def main():
  # prepare data
  trainingSet=df.values.tolist()[:18]
  testSet=df.values.tolist()[19:]
  
  print ('Train set: ' + repr(len(trainingSet)))
  print ('Test set: ' + repr(len(testSet)))

  # generate predictions
  predictions=[]
  k = 3
  for x in range(len(testSet)):
    neighbors = getNeighbors(trainingSet, testSet[x], k)
    result = getResponse(neighbors)
    predictions.append(result)
    print('> predicted=' + repr(result) + ', actual=' + repr(testSet[x][-1]))
  accuracy = getAccuracy(testSet, predictions)
  print('Accuracy: ' + repr(accuracy) + '%')
	
main()