def train(args):
try:
inputs = []
targets = []
y = range(args.start,args.end+1)
if(args.db == 'u'):
dl = Data_Loader()
i,t = dl.getTargets(y)
elif(args.db == 'b'):
dl = Data_Loader()
i,t = dl.getBalancedTargets(y)
elif(args.db == 'p'):
dl = Data_Loader('playoffTeams.csv')
i,t = dl.getTargets(y)
elif(args.db == 'o'):
dl = Data_Loader('balancedData.csv')
i,t = dl.getTargets(y)
elif(args.db == 's'):
dl = Data_Loader()
i,t = dl.getBLSmoteTargets(y,.25)
#i,t = dl.getSmoteTargets(y)
inputs += i
targets += t
#create NN
# if file already exists, build on that training
if (os.path.exists(args.file)):
print "file exists"
nn = Neural_Network.createFromFile(args.file)
pass
else:
print "file does not exist"
nn = Neural_Network.createWithRandomWeights(len(inputs[0]),args.nodes,len(targets[0]))
#train NN with the given data
print 'Beginning Training...'
nn = nn.train(args.epochs,inputs,targets,args.learn_rate)
nn.saveToFile(args.file)
print "Neural Network saved to %s" % (args.file)
except Exception as e:
print "invalid formatting, consult neural_main.py t --help \n Error: %s" % e
