settings.online = True nodes = 200 lr = 0.003#231262326395 settings.nodes = nodes settings.batch_size = 128 settings.lr = lr settings.loss = 'mae' settings.stateful=False settings.lookback = 50 settings.lookback_as_features=False settings.feature_count = 3 settings.predictionStep = 5 settings.season = 48 settings.adam_eps = 0.001 settings.retrain_interval = 1000 settings.reset_on_retrain = False settings.refeed_on_retrain = True settings.cutoff_normalize = True settings.use_dropout = True settings.nTrain = 5000 settings.ignore_for_error = [5500,10000] settings.normalization_type = 'default' settings.implementation = 'keras' settings.rnn_type = 'lstm' settings.use_binary = False settings.limit_to = None settings.finalize() mase = run_gru(settings) print mase
except:
settings.lookback = None
settings.nodes = int(argv[3])
try:
settings.batch_size = int(argv[9])
except:
settings.batch_size = None
settings.retrain_interval = int(argv[4])
settings.lookback_as_features = True if argv[10] == "True" else False
settings.feature_count = int(argv[11])
settings.lr = float(argv[5])
settings.predictionStep = 5
settings.season = 48
settings.ignore_for_error = [5500]
settings.nTrain = 5000
settings.limit_to = 7500 # if not
settings.normalization_type = 'default'
settings.implementation = 'keras'
settings.rnn_type = argv[12]
settings.use_binary = False
settings.stateful = False
settings.adam_eps = float(argv[13])
settings.refeed_on_retrain = True
settings.reset_on_retrain = False
settings.use_dropout = False
settings.finalize()
mase = run_gru(settings)
print str(mase)