Classifier with the firstname

fts = {}

cls = {}

for gender in genders:

fts_names = Feature(firstnames[gender], name=gender)

cls[gender] = NBclass(gender, fts_names)

c = Classifier(cls["male"], cls["female"])

testnames = ['Edgar', 'Benjamin', 'Fred', 'Albert', 'Laura',

'Maria', 'Paula', 'Sharon', 'Jessie']

for name in testnames:

print(name, c.prob(name))

Results:

Edgar (0.5, 'male')

Benjamin (1.0, 'male')

Fred (1.0, 'male')

Albert (1.0, 'male')

Laura (1.0, 'female')

Maria (1.0, 'female')

Paula (1.0, 'female')

Sharon (1.0, 'female')

Jessie (0.6666666666666667, 'female')