def main():
db_helper = ApeicDBHelper()
users = db_helper.get_users()
for user in users:
logs = db_helper.get_logs(user)
preprocessor = Preprocessor(logs)
preprocessor.extract_stay_points()
def main():
db_helper = ApeicDBHelper()
users = db_helper.get_users()
for user in users:
logs = db_helper.get_logs(user)
preprocessor = Preprocessor(logs)
preprocessor.extract_stay_points()
def main():
# TODO: ignore some user's data?
db = ApeicDBHelper()
logs = []
for user in db.get_users():
logs.extend(db.get_logs(user))
analyzer = RealDataAnalyzer()
analyzer.get_env_context_distrs(logs)
def main():
# TODO: ignore some user's data?
db = ApeicDBHelper()
logs = []
for user in db.get_users():
logs.extend(db.get_logs(user))
analyzer = RealDataAnalyzer()
analyzer.get_env_context_distrs(logs)
def main():
db_helper = ApeicDBHelper()
hits = 0.0
misses = 0.0
users = db_helper.get_users()
for user in users:
logs = db_helper.get_logs(user)
training_data, testing_data = split(logs)
predictor = TAPPredictor()
predictor.train(training_data)
for i in xrange(2, len(testing_data)):
candidates = predictor.predict(testing_data[i-2]['application'], testing_data[i-1]['application'], k)
if testing_data[i]['application'] in candidates:
hits += 1.0
else:
misses += 1.0
print k, hits/(hits + misses)
def main(): db_helper = ApeicDBHelper() users = db_helper.get_users() accuracies = [] for user in users: if user == '11d1ef9f845ec10e': continue print colored(user, attrs=['blink']) logs = db_helper.get_logs(user) predictor = APPRushPredictor() training_logs, testing_logs = predictor.split(logs, 0.8) predictor.train(training_logs) hits = 0.0 misses = 0.0 # testing_logs = training_logs last_log = testing_logs[0] for log in testing_logs[1:]: if log['application'] != last_log['application'] or log['id'] == testing_logs[-1]['id']: candidates = predictor.predict(last_log, log, 5) if log['application'] in candidates: hits += 1 else: misses += 1 last_log = log acc = hits/(hits + misses) accuracies.append(acc) print acc print sum(accuracies)/len(accuracies)
def main():
db_helper = ApeicDBHelper()
users = db_helper.get_users()
accuracies = []
for user in users:
if user == '11d1ef9f845ec10e':
continue
print colored(user, attrs=['blink'])
logs = db_helper.get_logs(user)
predictor = APPRushPredictor()
training_logs, testing_logs = predictor.split(logs, 0.8)
predictor.train(training_logs)
hits = 0.0
misses = 0.0
# testing_logs = training_logs
last_log = testing_logs[0]
for log in testing_logs[1:]:
if log['application'] != last_log['application'] or log[
'id'] == testing_logs[-1]['id']:
candidates = predictor.predict(last_log, log, 5)
if log['application'] in candidates:
hits += 1
else:
misses += 1
last_log = log
acc = hits / (hits + misses)
accuracies.append(acc)
print acc
print sum(accuracies) / len(accuracies)
