naive bayes

Question 1

how does naive bayes make classification simpler

Answer 1

assumption simplifies the computation , making it easier to do classification tasks

Question 2

what is naive bayes

Answer 2

it is a simple porbabilistic classifier based on bayes theorem

Question 3

why is naive bayes ‘naive’

Answer 3

assumes features are given conditional independence based on the class label , hence the term ‘naive’

Question 4

what are the advantages of naive bayes

Answer 4

simple and easy to implement
fast training and prediction
works well with large data
preforms well with categorical ad continuous features

Question 5

applications of naive bayes

Answer 5

recommendation systems
document categorisation
medical diagnosis
text classification

Question 6

what are the disadvantages of naive bayes

Answer 6

can not preform as well with highly correlated features
‘naive’ assumption of feature independence is rarely true in practice
sensitive to imbalance data