def app_dlist(dlist, appID, clickTime, correlate, ad : Advertisement):
result = -1
for d in dlist:
if d['clickTime'] >= clickTime:
break
da = appID
db = ad.get_value(d['creativeID'])['appID']
_prod = get_prod(correlate, da, db, d['label'])
if _prod > result:
result = _prod
return result
import xgboost as xgb
from conf.configure import Configure
from reading.advertisement import Advertisement
from reading.app import App
from reading.dataset import Dataset
from reading.position import Position
from reading.user import User
from reading.user_app_actions import User_App_Actions
import matplotlib.pyplot as plt
import numpy as np
if __name__ == '__main__':
debug = False
print('reading data...')
ad = Advertisement(Configure.ad_path, debug=debug)
app = App(Configure.app_categories_path, debug=debug)
data_set = Dataset(Configure.train_path, Configure.test_path, debug=debug)
position = Position(Configure.position_path, debug=debug)
user = User(Configure.user_path, debug=debug)
user_app_actions = User_App_Actions(Configure.user_app_actions_path, debug=debug)
days = [0] * 32
hours = [0] * 24
minutes = [0] * 60
conver_days = [0] * 32
conver_hours = [0] * 24
conver_minutes = [0] * 60
click_in_con_days= [0] * 32
def add_to_app_cat(self, ad: Advertisement, app: App):
for record in self.data_list:
creativeID = record.creativeID
appID = ad.get_value(creativeID).appID
appCategory = app.get_value(appID).appCategory
app.add_dataset(record, appCategory)
def add_to_advertisement(self, ad: Advertisement):
for record in self.data_list:
ad.add_dataset(record)
ad.fresh()
def app_dlist(d, ad: Advertisement):
result = common_part(d)
result['condition'] = ad.get_value(d['creativeID'])['appID']
return result
from conf.configure import Configure
from reading.advertisement import Advertisement
from reading.app import App
from reading.dataset import Dataset
from reading.position import Position
from reading.user import User
from reading.user_app_actions import User_App_Actions
from reading.user_app_installed import User_App_Installed
from feature.dmatrix import DMatrix
from model.xgb_func import *
from handle.handle import *
if __name__ == '__main__':
debug = False
print('reading data...')
ad = Advertisement(Configure.ad_path, debug=debug)
data_set = Dataset(Configure.train_path, Configure.test_path, debug=debug)
user = User(Configure.user_path, debug=debug)
from_t = 290000
end_t = 310000
result = dict()
for d in data_set.get_data_list():
if d['clickTime'] < from_t or d['clickTime'] >= end_t:
continue
userID = d['userID']
baby = user.get_value(userID)['haveBaby']
creativeID = d['creativeID']
appID = ad.get_value(creativeID)['appID']
label = d['label']
if baby not in result:
result[tmp[0]][tmp[1]] = tmp[2:]
fin.close()
return result
def logloss(act, pred):
epsilon = 1e-15
pred = sp.maximum(epsilon, pred)
pred = sp.minimum(1 - epsilon, pred)
ll = sum(act * sp.log(pred) + sp.subtract(1, act) * sp.log(sp.subtract(1, pred)))
ll = ll * -1.0 / len(act)
return ll
if __name__ == '__main__':
debug = False
print('reading data...')
ad = Advertisement(Configure.ad_path, debug=debug)
app = App(Configure.app_categories_path, debug=debug)
data_set = Dataset(Configure.train_path, Configure.test_path, debug=debug)
position = Position(Configure.position_path, debug=debug)
user = User(Configure.user_path, debug=debug)
user_app_actions = User_App_Actions(Configure.user_app_actions_path, debug=debug)
# user_app_installed = User_App_Installed(Configure.user_installedapps_path, debug=debug)
data_set.add_to_position(position)
data_set.add_to_advertisement(ad)
data_set.add_to_app_cat(ad, app)
func_dict = {'creativeID': creative_dlist,
'adID': ad_dlist,
'camgaignID': camgaign_dlist,
'advertiserID': advertiser_dlist,
'appID': app_dlist,
import pandas as pd
from conf.configure import Configure
from reading.advertisement import Advertisement
from reading.dataset import Dataset
from reading.user import User
from reading.app import App
if __name__ == '__main__':
ad = Advertisement(Configure.ad_path)
app = App(Configure.app_categories_path)
data_set = Dataset(Configure.train_path, Configure.test_path)
user = User(Configure.user_path)
result0 = [0] * 100
result1 = [0] * 100
for d in data_set.get_data_list():
userID = d['userID']
age = user.get_value(userID)['age']
label = d['label']
if label < 0:
continue
if label == 0:
result0[age] += 1
else:
result1[age] += 1
for i in range(len(result0)):
print(i, result0[i] + result1[i], result0[i], result1[i])
from feature_role.lda_role import Lda_Role
from reading.dataset import Dataset
from conf.configure import Configure
from reading.advertisement import Advertisement
import numpy as np
if __name__ == '__main__':
data_set = Dataset(Configure.train_path, Configure.test_path)
ad = Advertisement(Configure.ad_path)
param = {'userID': 311729, 'appID': 420}
role = Lda_Role()
result = dict()
for d in data_set.get_data_list():
param = {
'userID': d['userID'],
'appID': ad.get_value(d['creativeID'])['appID']
}
vec = role.run(param)
clickDay = d['clickTime'] // 10000
label = d['label']
if label < 0:
label = 0
if clickDay not in result:
result[clickDay] = dict()
result[clickDay][0] = dict()
result[clickDay][1] = dict()
result[clickDay][0]['vec'] = np.zeros([len(vec)])
result[clickDay][0]['include_c'] = 0
result[clickDay][0]['exclude_c'] = 0
result[clickDay][1]['vec'] = np.zeros([len(vec)])
result[clickDay][1]['include_c'] = 0