Understanding Naive Bayes Classifier

If an email contains the word bu then what is the probability that this email is Spam given the data that we have?

• 40%

• 60%

• 80%

• 100%

If an email contains the word chip what is the probability it is spam?

• 40%

• 60%

• 80%

• 100%

What is the probability of an email being spam if it contains both the word buy and the word cheap?

If an email contains the word buy and cheap what is the probability to spam?

• 40

• 60

• 80

• 100

What would you do if you have the situation and you have to sort of imagine how many emails would contain the words buy and cheap?

In an ideal world where everything was pretty how many emails would contain the words buy and cheap?

What is 10% of 5%?

• 0.5%

• 1%

• 2%

• 3%

What assumption did we make about the words buy and cheap?