Question



Naive Bayes: How can we tell when to tune data?

Today in class we were told to: Apply naiveBayes to your train and test set of exercise 2 and compute the auc. Do you obtain a good or bad
auc? But how do we know if we need to tune the data?





Answers and follow-up questions





Answer or follow-up question 1

Dear student,

Can you elaborate on what you mean by `tune the data'?
If you mean to ask: `How do we know if we need to tune a model?', then the answer is: if the algorithm has parameters that require tuning.
These are all the parameters that we tune in class.

Naive Bayes does not require tuning.

Best,
Michel Ballings


Answer or follow-up question 2

When do we know which parameters of the model need tuning?
Thanks!


Answer or follow-up question 3

Dear student,

You need to tune all the parameters that have a large impact on the estimation process. These are all the parameters that we tune in the
book.

Best,
Michel Ballings



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