def __test(self):
db = get_db()
dataList = db.sampledata.find()
for data in dataList:
if data['name'] == self.__data_name:
self.__test_data = data['data']
self.__type = data['type']
break
resultList = db.result.find()
for result in resultList:
if result['name'] == self.__test_name:
self.__trees = result['trees']
break
count = 0
for data in self.__test_data:
vote = {}
for tree in self.__trees:
label = predict(tree, data)
if label not in vote.keys():
vote[label] = 0
vote[label] += 1
max = 0
majorityLabel = None
for label in vote.keys():
if vote[label] > max:
max = vote[label]
majorityLabel = label
if majorityLabel == self.__type:
count += 1
else:
self.__error_data.append(data)
self.__correct_rate = float(count) / len(self.__test_data)
def __test(self):
db = get_db()
dataList = db.sampledata.find()
for data in dataList:
if data['name'] == self.__data_name:
self.__test_data = data['data']
self.__type = data['type']
break
resultList = db.result.find()
for result in resultList:
if result['name'] == self.__test_name:
self.__trees = result['trees']
break
count = 0
for data in self.__test_data:
vote = {}
for tree in self.__trees:
label = predict(tree, data)
if label not in vote.keys():
vote[label] = 0
vote[label] += 1
max = 0
majorityLabel = None
for label in vote.keys():
if vote[label] > max:
max = vote[label]
majorityLabel = label
if majorityLabel == self.__type:
count += 1
else:
self.__error_data.append(data)
self.__correct_rate = float(count) / len(self.__test_data)
def __init__(self):
self.__db = get_db()
self.__dataList = self.__db.sampledata.find()
self.__dataDict = {}
for data in self.__dataList:
self.__dataDict[data['name']] = {
'type': data['type'],
'data': data['data'],
'name': data['name'],
}
def saveTrainResult(name, trees):
"""
save the training result
:param name: the name you want to save
:param trees: the list of decision trees
:return:
"""
trainResult = get_db().result
trainResult.insert({
'name': name,
'trees': trees,
})
def __init__(self):
self.__db = get_db()
self.__dataList = self.__db.sampledata.find()
self.__dataDict = {}
for data in self.__dataList:
self.__dataDict[data['name']] = {
'type': data['type'],
'data': data['data'],
'name': data['name'],
}
self.__resultList = self.__db.result.find()
self.__resultDict = {}
for result in self.__resultList:
self.__resultDict[result['name']] = {'trees': result['trees']}
def __init__(self):
self.__db = get_db()
self.__dataList = self.__db.sampledata.find()
self.__dataDict = {}
for data in self.__dataList:
self.__dataDict[data['name']] = {
'type' : data['type'],
'data' : data['data'],
'name' : data['name'],
}
self.__resultList = self.__db.result.find()
self.__resultDict = {}
for result in self.__resultList:
self.__resultDict[result['name']] = {
'trees' : result['trees']
}
def stop_sampling(self, client_mac, type):
"""
stop sampling the given client mac
:param client_mac: client mac you want to sample
:param type: the type of area you define
:return:
"""
self.__sampling = False
data = self.__dpm_proxy.delSampleMac(client_mac)
print 'sample_data:'
print data
# write into database
if len(data) != 0:
db = get_db()
sampleData = db.sampledata
sampleData.insert({
'name' : client_mac + '_' + type + '_' + time.strftime("%Y%m%d%H%M%S", time.localtime()),
'type' : type,
'data' : data
})
def stop_sampling(self, client_mac, type):
"""
stop sampling the given client mac
:param client_mac: client mac you want to sample
:param type: the type of area you define
:return:
"""
self.__sampling = False
data = self.__dpm_proxy.delSampleMac(client_mac)
print 'sample_data:'
print data
# write into database
if len(data) != 0:
db = get_db()
sampleData = db.sampledata
sampleData.insert({
'name':
client_mac + '_' + type + '_' +
time.strftime("%Y%m%d%H%M%S", time.localtime()),
'type':
type,
'data':
data
})