From Manfred Kerber's lecture notes.

Naive Bayes Approach

Let a list of attribute values [a1,a2,... ,an] be given, e.g., [Outlook=sunny, Humidity=high, Wind=strong] . The task is to predict a target concept PlayTennis in form of a yes/no decision.
 Day  Outlook  Temperature  Humidity  Wind  PlayTennis
-------- ------------- -------------
 D1  Sunny  Hot  High  Weak  No
 D2  Sunny  Hot  High  Strong  No
 D3  Overcast  Hot  High  Weak  Yes
 D4  Rain  Mild  High  Weak  Yes
 D5  Rain  Cool  Normal  Weak  Yes
 D6  Rain  Cool  Normal  Strong  No
 D7  Overcast  Cool  Normal  Strong  Yes
 D8  Sunny  Mild  High  Weak  No
 D9  Sunny  Cool  Normal  Weak  Yes
 D10  Rain  Mild  Normal  Weak  Yes
 D11  Sunny  Mild  Normal  Strong  Yes
 D12  Overcast  Mild  High  Strong  Yes
 D13  Rain  Hot  Normal  Weak  Yes
 D14  Rain  Mild  High  Strong  No

We see a new instance
 Day  Outlook  Temperature  Humidity  Wind  PlayTennis
-------- ------------- -------------
 new  Sunny  Cool  High  Strong  ???

How should it be classified?