guess = s.guess(args.name, binary=True, ml="gaussianNB")
elif (args.ml == "multinomialNB"):
guess = s.guess(args.name, binary=True, ml="multinomialNB")
elif (args.ml == "bernoulliNB"):
guess = s.guess(args.name, binary=True, ml="bernoulliNB")
if (guess == 1):
sex = "male"
elif (guess == 0):
sex = "female"
elif (guess == 2):
sex = "unknown"
print("%s gender is %s" % (str(args.name), sex))
else:
print("%s's gender is %s" % (str(args.name), s.guess(args.name)))
if (args.total == "ine"):
print("%s males for %s from INE.es" % (s.name_frec(args.name, dataset=args.total)['males'], args.name))
print("%s females for %s from INE.es" % (s.name_frec(args.name, dataset=args.total)['females'], args.name))
elif (args.total == "uscensus"):
print("%s males for %s from US Census (2017)" % (s.name_frec(args.name, dataset=args.total)['males'], args.name))
print("%s females for %s from US Census (2017)" % (s.name_frec(args.name, dataset=args.total)['females'], args.name))
elif (args.total == "ukcensus"):
print("%s males for %s from UK Census (2017)" % (s.name_frec(args.name, dataset=args.total)['males'], args.name))
print("%s females for %s from UK Census (2017)" % (s.name_frec(args.name, dataset=args.total)['females'], args.name))
elif (args.total == "all"):
males1 = s.name_frec(args.name, dataset="ine")['males']
males2 = s.name_frec(args.name, dataset="uscensus")['males']
males3 = s.name_frec(args.name, dataset="ukcensus")['males']
males = int(males1) + int(males2) + int(males3)
females1 = s.name_frec(args.name, dataset="ine")['females']
females2 = s.name_frec(args.name, dataset="uscensus")['females']
females3 = s.name_frec(args.name, dataset="ukcensus")['females']
print("gender: unknown")
print("you can try predict with --ml")
elif (args.total == "luciahelena"):
g = Gender()
males = g.csv2names(path="files/names/allnoundefined.males.csv")
females = g.csv2names(path="files/names/allnoundefined.females.csv")
print("%s was classified as: " % args.name)
if (args.name in males):
print("male")
elif (args.name in females):
print("female")
else:
print("this name was not classified as male or female")
elif ((args.verbose) or (args.total == "all")):
num_males = s.name_frec(args.name, dataset="ine")['males']
num_females = s.name_frec(args.name, dataset="ine")['females']
print("%s males for %s from INE.es" % (num_males, args.name))
print("%s females for %s from INE.es" % (num_females, args.name))
num_males = s.name_frec(args.name, dataset="uy")['males']
num_females = s.name_frec(args.name, dataset="uy")['females']
print("%s males for %s from Uruguay census" % (num_males, args.name))
print("%s females for %s from Uruguay census" % (num_females, args.name))
num_males = s.name_frec(args.name, dataset="uk")['males']
num_females = s.name_frec(args.name, dataset="uk")['females']
print("%s males for %s from United Kingdom census" %
(num_males, args.name))
print("%s females for %s from United Kingdom census" %
(num_females, args.name))
num_males = s.name_frec(args.name, dataset="us")['males']
num_females = s.name_frec(args.name, dataset="us")['females']
