defaultAlgoArgs.numRowSamples = 15 defaultAlgoArgs.parallelSGD = True defaultAlgoArgs.recordFolds = 1 defaultAlgoArgs.validationUsers = 0.0 # data args parser # dataParser = argparse.ArgumentParser(description="", add_help=False) dataParser.add_argument("-h", "--help", action="store_true", help="show this help message and exit") devNull, remainingArgs = dataParser.parse_known_args(namespace=dataArgs) if dataArgs.help: helpParser = argparse.ArgumentParser(description="", add_help=False, parents=[dataParser, RankingExpHelper.newAlgoParser(defaultAlgoArgs)]) helpParser.print_help() exit() #Create/load a low rank matrix X = DatasetUtils.epinions(minNnzRows=10) (m, n) = X.shape #For the moment, use a subsample #modelSelectSamples = 2*10**5 #X, userInds = Sampling.sampleUsers2(X, modelSelectSamples, prune=True) dataArgs.extendedDirName = "" dataArgs.extendedDirName += "Epinions" # print args # logging.info("Running on " + dataArgs.extendedDirName) logging.info("Data params:") keys = list(vars(dataArgs).keys()) keys.sort() for key in keys: