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']