save_to_file(fileNameWrite, recordedStats, tim)
timeRun = datetime.datetime.now().strftime('_%m_%d_%H_%M') # the current data time
fileSig = 'LastFM_100'
batchSize = 50 # size of one batch
d = 25 # feature dimension
alpha = 0.3 # control how much to explore
lambda_ = 0.2 # regularization used in matrix A
Gepsilon = 0.3 # Parameter in initializing GW
totalObservations = 0
userNum = 100
W = initializeW(userNum, LastFM_relationFileName) # Generate user relation matrix
GW = initializeGW(Gepsilon, userNum, LastFM_relationFileName)
articles_random = randomStruct()
CoLinUCB_USERS = CoLinUCBStruct(d, lambda_, userNum, W)
GOBLin_USERS = GOBLinStruct(d, lambda_, userNum, GW)
LinUCB_users = []
for i in range(userNum):
LinUCB_users.append(LinUCBStruct(d, lambda_))
fileName = LastFM_address + "/processed_events.dat"
fileNameWrite = os.path.join(LastFM_save_address, fileSig + timeRun + '.csv')
# FeatureVectorsFileName = LastFM_address + '/Arm_FeatureVectors.dat'
# put some new data in file for readability
with open(fileNameWrite, 'a+') as f:
timeRun = datetime.datetime.now().strftime('_%m_%d_%H_%M') # the current data time
fileSig = 'Delicious_100_shuffled'
batchSize = 50 # size of one batch
d = 25 # feature dimension
alpha = 0.3 # control how much to explore
lambda_ = 0.2 # regularization used in matrix A
Gepsilon = 0.3 # Parameter in initializing GW
totalObservations = 0
userNum = 100
W = initializeW(userNum, Delicious_relationFileName) # Generate user relation matrix
GW = initializeGW(Gepsilon,userNum,Delicious_relationFileName)
articles_random = randomStruct()
CoLinUCB_USERS = CoLinUCBStruct(d, lambda_ ,userNum, W)
GOBLin_USERS = GOBLinStruct(d, lambda_, userNum, GW)
LinUCB_users = []
for i in range(userNum):
LinUCB_users.append(LinUCBStruct(d, lambda_ ))
fileName = Delicious_address + "/processed_events_shuffled.dat"
fileNameWrite = os.path.join(Delicious_save_address, fileSig + timeRun + '.csv')
#FeatureVectorsFileName = LastFM_address + '/Arm_FeatureVectors.dat'
# put some new data in file for readability
with open(fileNameWrite, 'a+') as f:
timeRun = datetime.datetime.now().strftime('_%m_%d_%H_%M') # the current data time
fileSig = 'LastFM_100'
batchSize = 50 # size of one batch
d = 25 # feature dimension
alpha = 0.3 # control how much to explore
lambda_ = 0.2 # regularization used in matrix A
Gepsilon = 0.3 # Parameter in initializing GW
totalObservations = 0
userNum = 100
W = initializeW(userNum, LastFM_relationFileName) # Generate user relation matrix
GW = initializeGW(Gepsilon,userNum, LastFM_relationFileName)
articles_random = randomStruct()
CoLinUCB_USERS = CoLinUCBStruct(d, lambda_ ,userNum, W)
GOBLin_USERS = GOBLinStruct(d, lambda_, userNum, GW)
LinUCB_users = []
for i in range(userNum):
LinUCB_users.append(LinUCBStruct(d, lambda_ ))
fileName = LastFM_address + "/processed_events.dat"
fileNameWrite = os.path.join(LastFM_save_address, fileSig + timeRun + '.csv')
#FeatureVectorsFileName = LastFM_address + '/Arm_FeatureVectors.dat'
# put some new data in file for readability
with open(fileNameWrite, 'a+') as f:
