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: