parser.add_argument('-n', action='store_true', help='Runs the naive algorithm')
parser.add_argument('-m', action='store_true', help='Computes Majority Vote')
args = parser.parse_args()
alphabet = "a b c"
types = alphabet.split()
numCharacters = len(types)
accuracies = []
cross_entropies = []
for sim in range(100): # Run 100 simulations
data = init_from_file("Tests/RareClass/data/%d.txt" % sim, 0, not args.r, True)
if args.m:
acc = MV(data)
print "Simulation %d: %.2f" % (sim, acc)
elif args.n:
acc = naive(data)
print "Simulation %d: %.2f" % (sim, acc)
else:
EM(data)
acc = data.best_percent_correct()
ce = data.best_cross_entropy()
print "Simulation %d: %.2f % | %.2f CE" % (sim, acc, ce)
cross_entropies.append(ce)
accuracies.append(acc)
elif (run_name == "CATD"):
#CATD
print("%s Day %d:" % (run_name, day))
e2wl, w2el, label_set = CATD.gete2wlandw2el("./data/"+now_work+"/%s/answers/%d/answer_%d.csv" % (rate, time, day))
print('读入数据完毕')
truth, weight = CATD.Conf_Aware(e2wl, w2el, 'categorical').Run(0.05,100)
print('EM完毕')
accurate3(truth, day, time, rate)
#accurate2(e2wl, w2el, label_set, truth, day, time, rate)
print('acc计算完毕')
elif (run_name == "MV"):
#MV
print("%s Day %d:" % (run_name, day))
e2wl, w2el, label_set = MV.gete2wlandw2el("./data/"+now_work+"/%s/answers/%d/answer_%d.csv" % (rate, time, day))
print('读入数据完毕')
e2lpd = MV.MV(e2wl, w2el, label_set).Run()
print('EM完毕')
truth = get_truth(e2lpd)
print('get真相完毕')
accurate3(truth, day, time, rate)
#accurate2(e2wl, w2el, label_set, truth, day, time, rate)
print('acc计算完毕')
elif (run_name == "PM"):
# PM
print("%s Day %d:" % (run_name, day))
e2wl, w2el, label_set = PM.gete2wlandw2el("./data/"+now_work+"/%s/answers/%d/answer_%d.csv" % (rate, time, day))
print('读入数据完毕')
e2lpd, weight = PM.CRH(e2wl, w2el, label_set, 'categorical', r'0/1 loss').Run(10)
print('EM完毕')
truth = get_truth(e2lpd)
print('get真相完毕')
