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: