I am reading naive Bayes classifier from the book "Data mining practical machine learning tools and techniques". The example of naive Bayes is given using the below dataset.
As (Outlook=Overcast | Play=No) has 0 counts, the book suggests using Laplace smoothing. For this, I have to add 1 to numerator and 3 to the denominator (as there are 3 different outlooks. I understand this part).
Now my question is do I have to use Laplace smoothing on (Outlook | Play=Yes) too? Do I have to use Laplace smoothing for other attributes too? Or using Laplace smoothing on only the attributes that have 0 count enough? (in this case (Outlook | Play=No)).