def main():
path = "/".join(os.getcwd().split("\\"))
data_list = load_dataset(path + "/Data/wine_data.txt")
navieBayes = NaiveBayes.NavieBayes()
x_train, x_test, y_train, y_test = navieBayes.pre_data_handle(data_list, ratio=0.3, random_state=5)
prob_num_dict, prob_dict = navieBayes.train(x_train, y_train, class_num=3)
y_predict = navieBayes.classify(prob_num_dict, prob_dict, x_test, class_num=3)
disp_result(y_test, y_predict)
right_rate = navieBayes.calc_right_rate(y_test, y_predict)
print("Right rate:" + str(right_rate))
x_data = ['10.58', '2.26', '2.69', '24.5', '80', '1.55', '.84', '.39', '0.9', '8.66', '.74', '1.8', '600']
x_data_float = np.float32(x_data)
y_predict = navieBayes.predict(prob_num_dict, prob_dict, x_data_float, class_num=3)
print("测试数据："+str(x_data))
print("预测类别：" + str(y_predict))
