In this illustrative data set below, there are four categorical predictors, namely, "Outlook" (X1), "Temp" (X2), "Humidity" (X3), and "Windy" (X4), which describe the weather conditions of 14 different days (observations, i.e., rows of the table). The goal is to model whether ("Play" = Yes) or not ("Play" = No) a particular day is suitable to play. Variable "Play" is our dependent variable (Y), and since it takes on two possible values only, this is a binary classification problem. Consider the "Outlook" (X1 = Rainy), "Temp" (X2 = Mild), "Humidity" (X3 = Normal), and "Windy" (X4 = False), is this weather condition suitable for playing? Please use Nave Bayes to model this problem. Note that the calculation process (Nave Bayes probability table and calculation based on Nave Bayes formula) is required for this question.

Outlook Temp Humidity Windy Play Sunny Hot High False No Sunny Hot High True No Overcast Hot High False Yes Rainy Mild High False Yes Rainy Cool Normal False Yes Rainy Cool Normal True No Overcast Cool Normal True Yes Sunny Mild High False No Sunny Cool Normal False Yes Rainy Mild Normal False Yes Sunny Mild Normal True Yes Overcast Mild High True Yes Overcast Hot Normal False Yes Rainy Mild High True No