def command_line():
args = parser.parse_args()
if (args.validation):
if (args.kfolds):
fin = get_file(args.trainx[0])
finy = get_file(args.trainy[0])
if (args.method and args.method[0] == 'forest'):
kcrossvalidation.do_kcross_validation(fin, finy,
int(args.kfolds[0]))
if (args.testx):
fin = get_file(args.trainx[0])
finy = get_file(args.trainy[0])
(training,
validation) = get_training_validation_set(fin,
finy,
training_start=0,
training_end=2500,
validation_start=0,
validation_end=1)
if (args.method and args.method[0] == 'forest'):
forest = train_randomized_forest(training)
classify_output(forest, treerandom)
#print "accuracy : " + str(accuracy(validation,forest, treerandom))
print "done"
def run_k_times(k=1):
for i in range(0,k):
fin = get_file("trainx.txt")
finy = get_file("trainy.csv")
kcrossvalidation.do_kcross_validation(fin,finy,10)
#kcrossvalidation.do_simpletree_kcross_validation(fin,finy,5)
#(training,validation) = get_training_validation_set(fin,finy,training_start=0,training_end=2500,validation_start=2000,validation_end=2500)
#tree = train_simple_tree(training)
#treepredict.prune(tree,1)
#print "accuracy : " + str(accuracy(validation,tree, treepredict))
#forest = train_randomized_forest(training)
#print "accuracy : " + str(accuracy(validation,forest, treerandom))
#big_forest = train_big_randomized_forest(training)
#print "accuracy : " + str(accuracy(validation,big_forest, big_treerandom))
#classify_output(forest, treerandom)
#classify_output(forest, big_treerandom)
fin.close()
finy.close()
def run_k_times(k=1):
for i in range(0, k):
fin = get_file("trainx.txt")
finy = get_file("trainy.csv")
kcrossvalidation.do_kcross_validation(fin, finy, 10)
#kcrossvalidation.do_simpletree_kcross_validation(fin,finy,5)
#(training,validation) = get_training_validation_set(fin,finy,training_start=0,training_end=2500,validation_start=2000,validation_end=2500)
#tree = train_simple_tree(training)
#treepredict.prune(tree,1)
#print "accuracy : " + str(accuracy(validation,tree, treepredict))
#forest = train_randomized_forest(training)
#print "accuracy : " + str(accuracy(validation,forest, treerandom))
#big_forest = train_big_randomized_forest(training)
#print "accuracy : " + str(accuracy(validation,big_forest, big_treerandom))
#classify_output(forest, treerandom)
#classify_output(forest, big_treerandom)
fin.close()
finy.close()
def command_line():
args = parser.parse_args()
if(args.validation):
if(args.kfolds):
fin = get_file(args.trainx[0])
finy = get_file(args.trainy[0])
if(args.method and args.method[0]=='forest'):
kcrossvalidation.do_kcross_validation(fin,finy,int(args.kfolds[0]))
if(args.testx):
fin = get_file(args.trainx[0])
finy = get_file(args.trainy[0])
(training,validation) = get_training_validation_set(fin,finy,training_start=0,training_end=2500,validation_start=0,validation_end=1)
if(args.method and args.method[0]=='forest'):
forest = train_randomized_forest(training)
classify_output(forest, treerandom)
#print "accuracy : " + str(accuracy(validation,forest, treerandom))
print "done"
