def setUp(self):
self.config = {
"method": "PA1",
"converter": {
"string_filter_types": {},
"string_filter_rules": [],
"num_filter_types": {},
"num_filter_rules": [],
"string_types": {},
"string_rules": [{
"key": "*",
"type": "str",
"sample_weight": "bin",
"global_weight": "bin"
}],
"num_types": {},
"num_rules": [{
"key": "*",
"type": "num"
}]
},
"parameter": {
"sensitivity": 0.1,
"regularization_weight": 3.402823e+38
}
}
TestUtil.write_file('config_regression.json', json.dumps(self.config))
self.srv = TestUtil.fork_process('regression', port,
'config_regression.json')
try:
self.cli = Regression(host, port, "name")
except:
TestUtil.kill_process(self.srv)
raise
def main():
args = parse_options()
client = Regression('127.0.0.1', 9199, '')
# train
num = 0
if args.traindata:
with open(args.traindata, 'r') as traindata:
for data in traindata:
# skip comments
if not len(data) or data.startswith('#'):
continue
num += 1
rent, distance, space, age, stair, aspect = map(str.strip, data.strip().split(','))
d = Datum({
'aspect': aspect,
'distance': float(distance),
'space': float(space),
'age': float(age),
'stair': float(stair) })
train_data = [[float(rent), d]]
# train
client.train(train_data)
# print train number
print 'train ...', num
# anaylze
with open(args.analyzedata, 'r') as analyzedata:
myhome = yaml.load(analyzedata)
d = Datum({
'aspect': str(myhome['aspect']),
'distance': float(myhome['distance']),
'space': float(myhome['space']),
'age': float(myhome['age']),
'stair': float(myhome['stair'])
})
analyze_data = [d]
result = client.estimate(analyze_data)
print 'rent ....', round(result[0], 1)
