def main(neutral): get_documents(15, neutral) """for element in training_list: print element.vector print element.opinion""" result = training_nb(true_list, neutral) print apply_nb(result, "I do not really like this film", neutral)
def store_training(neutral): if neutral: database_name = "database3" else: database_name = "database2" get_documents(15, neutral) training_result = training_nb(true_list, neutral) with open(database_name, 'wb') as file: my_pickler = pickle.Pickler(file) my_pickler.dump(training_result)
def main(neutral): get_documents(15, neutral) """for element in training_list: print element.vector print element.opinion""" result = training_nb(true_list, neutral) print apply_nb(result, "I do not really like this film", neutral) neutral = False # main(neutral) get_documents(15, neutral) #print cross_validation(25, 98) print cross_validation(2, 98, neutral) result = 0 maximum = 0 count = 0 i_max = 0 j_max = 0 for j in range(1, 10): for i in range(60, 98): result = cross_validation(j, i, neutral) if result > maximum: maximum = result
def main(neutral): get_documents(15, neutral) """for element in training_list: print element.vector print element.opinion""" result = training_nb(true_list, neutral) print apply_nb(result, "I do not really like this film", neutral) neutral = False # main(neutral) get_documents(15, neutral) #print cross_validation(25, 98) print cross_validation(2, 98, neutral) result = 0 maximum = 0 count = 0 i_max = 0 j_max = 0 for j in range(1, 10): for i in range(60,98): result = cross_validation(j, i, neutral) if result > maximum: