def process(parse_result):
'''
desc: This function is used to process the analyzing of results
params: the instance returned by function--parser()
return: None
date: 2013-10-30
'''
dest_file = "../data/results.analysis"
input_file = parse_result.input_file.strip()
if os.path.isfile(input_file):
flag = 0
if parse_result.dest_file:
dest_file = parse_result.dest_file.strip()
flag = 1
tms.tms_analysis(input_file,
step=2,
output_file=dest_file,
indexes=[0, 1, 2],
predicted_label_index=0,
predicted_value_index=1,
true_label_index=2)
if flag == 0:
with open('../data/results.analysis') as f:
print f.read()
else:
print "输入文件不存在！\n"
def process(parse_result):
'''
desc: This function is used to process the analyzing of results
params: the instance returned by function--parser()
return: None
date: 2013-10-30
'''
dest_file="../data/results.analysis"
input_file = parse_result.input_file.strip()
if os.path.isfile(input_file):
flag=0
if parse_result.dest_file:
dest_file=parse_result.dest_file.strip()
flag=1
tms.tms_analysis(input_file,step=2,output_file=dest_file,indexes=[0,1,2],predicted_label_index=0,predicted_value_index=1,true_label_index=2)
if flag==0:
with open('../data/results.analysis') as f:
print f.read()
else:
print "输入文件不存在！\n"
def analysis(filename, step):
tms.tms_analysis(filename, step=step)
#!/usr/bin/python
import sys
sys.path.insert(
0,
"D:\\09Limited_buffer\\earlywarningbyci\\classification\\trainmodel\\src")
sys.path.insert(
0, "D:\\09Limited_buffer\\earlywarningbyci\\classification\\trainmodel\\")
import tms
#_*_ coding: utf-8 _*_
tms.tms_train("D:\\09Limited_buffer\\earlywarningbyci\\classification\\trainmodel\\data\\ad.txt",\
main_save_path="./data/",\
seg=1,indexes=[2],\
str_splitTag=" ",\
stopword_filename="./chinese_stopword.txt",\
ratio=1)
tms.tms_predict("D:\\09Limited_buffer\\earlywarningbyci\\classification\\trainmodel\\data\\adtrain3.txt","D:\\09Limited_buffer\\earlywarningbyci\\classification\\trainmodel\\data\\model\\tms.config",\
result_save_path="./data/pre.result",\
seg=1,\
indexes=[2])
tms.tms_analysis(".\\data\\pre.result")
def analysis(filename, step):
tms.tms_analysis(filename, step=step)
