def main():
#Simple argument consistency check
#Exit if arguments not specified
if len(sys.argv) != 3:
print("usage: python3 nblearn.py TRAININGFILE MODELFILE")
sys.exit(0)
#Create an instance of Naive Bayes class in training mode
naive_bayes = NB('TRAIN')
#Fit the data with the training file
naive_bayes.fit(sys.argv[1])
#Train the classifier
naive_bayes.train()
#Output a model file to the file specified
naive_bayes.generate_model(sys.argv[2])
zr = ZeroR()
zr.train(t, rows)
print("\ndiabetes")
zr.dump()
# NB
print("\n\n#--- Nbok ---------------------")
tbl = Tbl("weathernon.csv")
rows = []
for lst in tbl.fromString(False, "file"):
rows.append(lst)
c = Col()
tbl.cols = c.colNum(tbl.rows)
nb = NB(tbl, 3)
nb.train(tbl, rows)
print("\nweathernon")
nb.dump()
print()
tbl = Tbl("diabetes.csv")
rows = []
for lst in tbl.fromString(False, "file"):
rows.append(lst)
c = Col()
tbl.cols = c.colNum(tbl.rows)
nb = NB(tbl, 19)
nb.train(tbl, rows)
print("\ndiabetes")
nb.dump()
print('\n所有平均交叉结果:\n', round(sum(loss01)/len(loss01), 3))
if Global_V.SCHEME.upper() == 'KDB':
pass
if Global_V.SCHEME.upper() == 'AODE':
pass
if Global_V.SCHEME.upper() == 'NB':
result = []
fold_count = 0
for CrossTest_count in range(0, data_len, data_len // 10): # 交叉验证
p_c_fold = []
loss01_fold = 0
NB_data = NB(data_initial, 0.9, CrossTest_count)
NB_data.train()
p_c_fold, result_fold = NB_data.classify()
result.append(result_fold)
# print('\n第', fold_count, '次交叉结果：\n')
print('\n第', fold_count, '次交叉')
loss01_fold = estimate_Output(NB_data.testData, p_c_fold, result_fold, 1)
loss01.append(loss01_fold)
fold_count += 1
# 每个分类的过程，必须保存：1. 每一个testdata里的instance分类到每个Ci的概率p_y 2. 分类结果：result
# output(result, TAN_car.testData,1) # output 函数的输入为：
# output的输出，应该要有：1.每个testdata分到每个类的概率 2.分类结果result 3.testData，(以及参数1,2,3;不同的参数，输出不同)
# compare the prediction results with the real results
if Global_V.PRINTPAR == 3:
print('testset:\n', NB_data.testData, '\n')
print('p_ci= \n', p_c_fold, '\n', 'result:\n', result)
print('the first element is the result of prediction, second is real result!\n')
