Naive Bayes

If we are trying to classify if a person walks to work, or drives to work, we can use Bayes Theorom to get which of the following?

• Probability that the individual walks to work

• Probability that the individual drives to work

• A & B

• None of the above

In our NB equation, do we use the following? Prior Probability, Marginal Likelihood, Posterior Probability

• Yes

• No

In our example because we don't have too much information, how do we calculate P(Walks)

• We take the number of walkers divided by the total number of observations. In our example that is 10/30.

• We take the number of drivers and multiply it by the dependent variable.

• We take the number of walkers and add it to the total number of observations.

• None of the above

Is the following true: Bayes theorem requires independence assumption which are sometimes incorrect, so it is seen as "naive"

• Yes

• No

When we have more than 2 classes is the following statement true? It follows a similar/straight process as it always adds up to 1. If we have 3 classes and classify 1 and it's greater than 50% we can assign that class, but if not we have to calculate for each to assign the classification.

• Yes

• No