print([person for person in persons if person[0] == "Jessie"])
[['Jessie', 'Morgan', '175', '67.0', 'male'], ['Jessie', 'Bell', '165', '65', 'female'], ['Jessie', 'Washington', '159', '56', 'female'], ['Jessie', 'Davis', '174', '45', 'female'], ['Jessie', 'Johnson', '165', '30.0', 'male'], ['Jessie', 'Thomas', '168', '69', 'female']]
Jessie Washington is only 159 cm tall. If we have a look at the results of our Classifier, trained with heights, we see that the likelihood for a person 159 cm tall of being "female" is 0.875. So what about an unknown person called "Jessie" and being 159 cm tall? Is this person female or male?
To answer this question, we will train an Naive Bayes classifier with two feature classes, i.e. heights and firstnames: